Four Key Emerging Considerations with Artificial Intelligence (AI) in Cyber Security

#cryptonews #cyberrisk #techrisk #techinnovation #techyearinreview #infosec #musktwitter #disinformation #cio #ciso #cto #chatgpt #openai #airisk #iam #rbac #artificialintelligence #samaltman #aiethics #nistai #futurereadybusiness #futureofai

By Jeremy Swenson

Fig. 1. Zero Trust Components to Orchestration AI Mashup; Microsoft, 09/17/21; and Swenson, Jeremy, 03/29/24.

1. The Zero-Trust Security Model Becomes More Orchestrated via Artificial Intelligence (AI):

      The zero-trust model represents a paradigm shift in cybersecurity, advocating for the premise that no user or system, irrespective of their position within the corporate network, should be automatically trusted. This approach entails stringent enforcement of access controls and continual verification processes to validate the legitimacy of users and devices. By adopting a need-to-know-only access philosophy, often referred to as the principle of least privilege, organizations operate under the assumption of compromise, necessitating robust security measures at every level.

      Implementing a zero-trust framework involves a comprehensive overhaul of traditional security practices. It entails the adoption of single sign-on functionalities at the individual device level and the enhancement of multifactor authentication protocols. Additionally, it requires the implementation of advanced role-based access controls (RBAC), fortified network firewalls, and the formulation of refined need-to-know policies. Effective application whitelisting and blacklisting mechanisms, along with regular group membership reviews, play pivotal roles in bolstering security posture. Moreover, deploying state-of-the-art privileged access management (PAM) tools, such as CyberArk for password check out and vaulting, enables organizations to enhance toxic combination monitoring and reporting capabilities.

      App-to-app orchestration refers to the process of coordinating and managing interactions between different applications within a software ecosystem to achieve specific business objectives or workflows. It involves the seamless integration and synchronization of multiple applications to automate complex tasks or processes, facilitating efficient data flow and communication between them. Moreover, it aims to streamline and optimize various operational workflows by orchestrating interactions between disparate applications in a cohesive manner. This orchestration process typically involves defining the sequence of actions, dependencies, and data exchanges required to execute a particular task or workflow across multiple applications.

      However, while the concept of zero-trust offers a compelling vision for fortifying cybersecurity, its effective implementation relies on selecting and integrating the right technological components seamlessly within the existing infrastructure stack. This necessitates careful consideration to ensure that these components complement rather than undermine the orchestration of security measures. Nonetheless, there is optimism that the rapid development and deployment of AI-based custom middleware can mitigate potential complexities inherent in orchestrating zero-trust capabilities. Through automation and orchestration, these technologies aim to streamline security operations, ensuring that the pursuit of heightened security does not inadvertently introduce operational bottlenecks or obscure visibility through complexity.

      2. Artificial Intelligence (AI) Powered Threat Detection Has Improved Analytics:

      The utilization of artificial intelligence (AI) is on the rise to bolster threat detection capabilities. Through machine learning algorithms, extensive datasets are scrutinized to discern patterns suggestive of potential security risks. This facilitates swifter and more precise identification of malicious activities. Enhanced with refined machine learning algorithms, security information and event management (SIEM) systems are adept at pinpointing anomalies in network traffic, application logs, and data flow, thereby expediting the identification of potential security incidents for organizations.

      There will be reduced false positives which has been a sustained issue in the past with large overconfident companies repeatedly wasting millions of dollars per year fine tuning useless data security lakes that mostly produce garbage anomaly detection reports [1], [2]. Literally the kind good artificial intelligence (AI) laughs at – we are getting there. All the while, the technology vendors try to solve this via better SIEM functionality for an increased price at present. Yet we expect prices to drop really low as the automation matures.  

      With enhanced natural language processing (NLP) methodologies, artificial intelligence (AI) systems possess the capability to analyze unstructured data originating from various sources such as social media feeds, images, videos, and news articles. This proficiency enables organizations to compile valuable threat intelligence, staying abreast of indicators of compromise (IOCs) and emerging attack strategies. Notable vendors offering such services include Dark Trace, IBM, CrowdStrike, and numerous startups poised to enter the market. The landscape presents ample opportunities for innovation, necessitating the abandonment of past biases. Young, innovative minds well-versed in web 3.0 technologies hold significant value in this domain. Consequently, in the future, more companies are likely to opt for building their tailored threat detection tools, leveraging advancements in AI platform technology, rather than purchasing pre-existing solutions.

      3. Artificial Intelligence (AI) Driven Threat Response Ability Advances:

      Artificial intelligence (AI) isn’t just confined to threat detection; it’s increasingly playing a pivotal role in automating response actions within cybersecurity operations. This encompasses a range of tasks, including the automatic isolation of compromised systems, the blocking of malicious internet protocol (IP) addresses, the adjustment of firewall configurations, and the coordination of responses to cyber incidents—all achieved with greater efficiency and cost-effectiveness. By harnessing AI-driven algorithms, security orchestration, automation, and response (SOAR) platforms empower organizations to analyze and address security incidents swiftly and intelligently.

      SOAR platforms capitalize on AI capabilities to streamline incident response processes, enabling security teams to automate repetitive tasks and promptly react to evolving threats. These platforms leverage AI not only to detect anomalies but also to craft tailored responses, thereby enhancing the overall resilience of cybersecurity infrastructures. Leading examples of such platforms include Microsoft Sentinel, Rapid7 InsightConnect, and FortiSOAR, each exemplifying the fusion of AI-driven automation with comprehensive security orchestration capabilities.

      Microsoft Sentinel, for instance, utilizes AI algorithms to sift through vast volumes of security data, identifying potential threats and anomalies in real-time. It then orchestrates response actions, such as isolating compromised systems or blocking suspicious IP addresses, with precision and speed. Similarly, Rapid7 InsightConnect integrates AI-driven automation to streamline incident response workflows, enabling security teams to mitigate risks more effectively. FortiSOAR, on the other hand, offers a comprehensive suite of AI-powered tools for incident analysis, response automation, and threat intelligence correlation, empowering organizations to proactively defend against cyber threats. Basically, AI tools will help SOAR tools mature so security operations centers (SOCs) can catch the low hanging fruit; thus, they will have more time for analysis of more complex threats. These AI tools will employ the observe, orient, decide, act (OODA) Loop methodology [3]. This will allow them to stay up to date, customized, and informed of many zero-day exploits. At the same time, threat actors will constantly try to avert this with the same AI but with no governance.

        4. Artificial Intelligence (AI) Streamlines Cloud Security Posture Management (CSPM):

        With the escalating migration of organizations to cloud environments, safeguarding the security of cloud assets emerges as a paramount concern. While industry giants like Microsoft, Oracle, and Amazon Web Services (AWS) dominate this landscape with their comprehensive cloud offerings, numerous large organizations opt to establish and maintain their own cloud infrastructures to retain greater control over their data and operations. In response to the evolving security landscape, the adoption of cloud security posture management (CSPM) tools has become imperative for organizations seeking to effectively manage and fortify their cloud environments.

        CSPM tools play a pivotal role in enhancing the security posture of cloud infrastructures by facilitating continuous monitoring of configurations and swiftly identifying any misconfigurations that could potentially expose vulnerabilities. These tools operate by autonomously assessing cloud configurations against established security best practices, ensuring adherence to stringent compliance standards. Key facets of their functionality include the automatic identification of unnecessary open ports and the verification of proper encryption configurations, thereby mitigating the risk of unauthorized access and data breaches. “Keeping data safe in the cloud requires a layered defense that gives organizations clear visibility into the state of their data. This includes enabling organizations to monitor how each storage bucket is configured across all their storage services to ensure their data is not inadvertently exposed to unauthorized applications or users” [4]. This has considerations at both the cloud user and provider level especially considering artificial intelligence (AI) applications can be built and run inside the cloud for a variety of reasons. Importantly, these build designs often use approved plug ins from different vendors making it all the more complex.

        Furthermore, CSPM solutions enable organizations to proactively address security gaps and bolster their resilience against emerging threats in the dynamic cloud landscape. By providing real-time insights into the security status of cloud assets, these tools empower security teams to swiftly remediate vulnerabilities and enforce robust security controls. Additionally, CSPM platforms facilitate comprehensive compliance management by generating detailed reports and audit trails, facilitating adherence to regulatory requirements and industry standards.

        In essence, as organizations navigate the complexities of cloud adoption and seek to safeguard their digital assets, CSPM tools serve as indispensable allies in fortifying cloud security postures. By offering automated monitoring, proactive threat detection, and compliance management capabilities, these solutions empower organizations to embrace the transformative potential of cloud technologies while effectively mitigating associated security risks.

        About the Author:

        Jeremy Swenson is a disruptive-thinking security entrepreneur, futurist / researcher, and senior management tech risk consultant. He is a frequent speaker, published writer, podcaster, and even does some pro bono consulting in these areas. He holds an MBA from St. Mary’s University of MN, an MSST (Master of Science in Security Technologies) degree from the University of Minnesota, and a BA in political science from the University of Wisconsin Eau Claire. He is an alum of the Federal Reserve Secure Payment Task Force, the Crystal, Robbinsdale and New Hope Citizens Police Academy, and the Minneapolis FBI Citizens Academy.

        References:


        [1] Tobin, Donal; “What Challenges Are Hindering the Success of Your Data Lake Initiative?” Integrate.io. 10/05/22: https://www.integrate.io/blog/data-lake-initiative/

        [2] Chuvakin, Anton; “Why Your Security Data Lake Project Will … Well, Actually …” Medium. 10/22/22. https://medium.com/anton-on-security/why-your-security-data-lake-project-will-well-actually-78e0e360c292

        [3] Michael, Katina, Abbas, Roba, and Roussos, George; “AI in Cybersecurity: The Paradox.” IEEE Transactions on Technology and Society. Vol. 4, no. 2: pg. 104-109. 2023: https://ieeexplore.ieee.org/abstract/document/10153442

        [4] Rosencrance, Linda; “How to choose the best cloud security posture management tools.” CSO Online. 10/30/23: https://www.csoonline.com/article/657138/how-to-choose-the-best-cloud-security-posture-management-tools.html

        NIST Cybersecurity Framework (CSF) New Version 2.0 Summary

        Fig. 1. NIST CSF 2.0 Stepper, NIST, 2024.

        #cyberresilience #cybersecurity #generativeai #cyberthreats #enterprisearchitecture #CIO #CTO #riskmanagement #bias #governance #RBAC #CybersecurityFramework #Cybersecurity #NISTCSF #RiskManagement #DigitalResilience #nist #nistframework #cyberawareness

        The National Institute of Standards and Technology (NIST) has updated its widely used Cybersecurity Framework (CSF) — a free respected landmark guidance document for reducing cybersecurity risk. However, it’s important to note that most of the framework core has remained the same. Here are the core components the security community knows:

        Govern (GV): Sets forth the strategic path and guidelines for managing cybersecurity risks, ensuring harmony with business goals and adherence to legal requirements and standards. This is the newest addition which was inferred before but is specifically illustrated to touch every aspect of the framework. It seeks to establish and monitor your company’s cybersecurity risk management strategy, expectations, and policy.

        1.      Identify (ID): Entails cultivating a comprehensive organizational comprehension of managing cybersecurity risks to systems, assets, data, and capabilities.

        2.      Protect (PR): Concentrates on deploying suitable measures to guarantee the provision of vital services.

        3.      Detect (DE): Specifies the actions for recognizing the onset of a cybersecurity incident.

        4.      Respond (RS): Outlines the actions to take in the event of a cybersecurity incident.

        5.      Recover (RC): Focuses on restoring capabilities or services that were impaired due to a cybersecurity incident.

        The new 2.0 edition is structured for all audiences, industry sectors, and organization types, from the smallest startups and nonprofits to the largest corporations and government departments — regardless of their level of cybersecurity preparedness and complexity.

        Fig. 2. NIST CSF 2.0 Function Breakdown, NIST, 2024.

        Here are some key updates:

        Emphasis is placed on the framework’s expanded scope, extending beyond critical infrastructure to encompass all organizations. Importantly, it better incorporates and expands upon supply chain risk management processes. It also introduces a new focus on governance, highlighting cybersecurity as a critical enterprise risk with many dependencies. This is critically important with the emergence of artificial intelligence.

        To make it easier for a wide variety of organizations to implement the CSF 2.0, NIST has developed quick-start guides customized for various audiences, along with case studies showcasing successful implementations, and a searchable catalog of references, all aimed at facilitating the adoption of CSF 2.0 by diverse organizations.

        The CSF 2.0 is aligned with the National Cybersecurity Strategy and includes a suite of resources to adapt to evolving cybersecurity needs, emphasizing a comprehensive approach to managing cybersecurity risk. New adopters can benefit from implementation examples and quick-start guides tailored to specific user types, facilitating easier integration into their cybersecurity practices. The CSF 2.0 Reference Tool simplifies implementation, enabling users to access, search, and export core guidance data in user-friendly and machine-readable formats. A searchable catalog of references allows organizations to cross-reference their actions with the CSF, linking to over 50 other cybersecurity documents – facilitating comprehensive risk management. The Cybersecurity and Privacy Reference Tool (CPRT) contextualizes NIST resources with other popular references, facilitating communication across all levels of an organization.

        NIST aims to continually enhance CSF resources based on community feedback, encouraging users to share their experiences to improve collective understanding and management of cybersecurity risk. The CSF’s international adoption is significant, with translations of previous versions into 13 languages. NIST expects CSF 2.0 to follow suit, further expanding its global reach. NIST’s collaboration with ISO/IEC aligns cybersecurity frameworks internationally, enabling organizations to utilize CSF functions in conjunction with ISO/IEC resources for comprehensive cybersecurity management.

        Resources:

        1. NIST CSF 2.0 Fact Sheet.
        2. NIST CSF 2.0 PDF.
        3. NIST CSF 2.0 Reference Tool.
        4. NIST CSF 2.0 YouTube Breakdown.

        About the Author:

        Jeremy Swenson is a disruptive-thinking security entrepreneur, futurist/researcher, and senior management tech risk consultant. He is a frequent speaker, published writer, podcaster, and even does some pro bono consulting in these areas. He holds an MBA from St. Mary’s University of MN, an MSST (Master of Science in Security Technologies) degree from the University of Minnesota, and a BA in political science from the University of Wisconsin Eau Claire. He is an alum of the Federal Reserve Secure Payment Task Force, the Crystal, Robbinsdale and New Hope Citizens Police Academy, and the Minneapolis FBI Citizens Academy.

        Top Pros and Cons of Disruptive Artificial Intelligence (AI) in InfoSec

        Fig. 1. Swenson, Jeremy, Stock; AI and InfoSec Trade-offs. 2024.

        Disruptive technology refers to innovations or advancements that significantly alter the existing market landscape by displacing established technologies, products, or services, often leading to the transformation of entire industries. These innovations introduce novel approaches, functionalities, or business models that challenge traditional practices, creating a substantial impact on how businesses operate (ChatGPT, 2024). Disruptive technologies typically emerge rapidly, offering unique solutions that are more efficient, cost-effective, or user-friendly than their predecessors.

        The disruptive nature of these technologies often leads to a shift in market dynamics, digital cameras or smartphones for example. These with new entrants or previously marginalized players gain prominence while established entities may face challenges in adapting to the transformative changes (ChatGPT, 2024). Examples of disruptive technologies include the advent of the internet, mobile technology, and artificial intelligence (AI), each reshaping industries and societal norms. Here are four of the leading AI tools:

        1.       OpenAI’s GPT:

        OpenAI’s GPT (Generative Pre-trained Transformer) models, including GPT-3 and GPT-2, are predecessors to ChatGPT. These models are known for their large-scale language understanding and generation capabilities. GPT-3, in particular, is one of the most advanced language models, featuring 175 billion parameters.

        2.       Microsoft’s DialoGPT:

        DialoGPT is a conversational AI model developed by Microsoft. It is an extension of the GPT architecture but fine-tuned specifically for engaging in multi-turn conversations. DialoGPT exhibits improved dialogue coherence and contextual understanding, making it a competitor in the chatbot space.

        3.       Facebook’s BlenderBot:

        BlenderBot is a conversational AI model developed by Facebook. It aims to address the challenges of maintaining coherent and contextually relevant conversations. BlenderBot is trained using a diverse range of conversations and exhibits improved performance in generating human-like responses in chat-based interactions.

        4.       Rasa:

        Rasa is an open-source conversational AI platform that focuses on building chatbots and voice assistants. Unlike some other models that are pre-trained on large datasets, Rasa allows developers to train models specific to their use cases and customize the behavior of the chatbot. It is known for its flexibility and control over the conversation flow.

        Here is a list of the pros and cons of AI-based infosec capabilities.

        Pros of AI in InfoSec:

        1. Improved Threat Detection:

        AI enables quicker and more accurate detection of cybersecurity threats by analyzing vast amounts of data in real-time and identifying patterns indicative of malicious activities. Security orchestration, automation, and response (SOAR) platforms leverage AI to analyze and respond to security incidents, allowing security teams to automate routine tasks and respond more rapidly to emerging threats. Microsoft Sentinel, Rapid7 InsightConnect, and FortiSOAR are just a few of the current examples

        2. Behavioral Analysis:

        AI can perform behavioral analysis to identify anomalies in user behavior or network activities, helping detect insider threats or sophisticated attacks that may go unnoticed by traditional security measures. Behavioral biometrics, such as analyzing typing patterns, mouse movements and ram usage, can add an extra layer of security by recognizing the unique behavior of legitimate users. Systems that use AI to analyze user behavior can detect and flag suspicious activity, such as an unauthorized user attempting to access an account or escalate a privilege.

        3. Enhanced Phishing Detection:

        AI algorithms can analyze email patterns and content to identify and block phishing attempts more effectively, reducing the likelihood of successful social engineering attacks.

        4. Automation of Routine Tasks:

        AI can automate repetitive and routine tasks, allowing cybersecurity professionals to focus on more complex issues. This helps enhance efficiency and reduces the risk of human error.

        5. Adaptive Defense Systems:

        AI-powered security systems can adapt to evolving threats by continuously learning and updating their defense mechanisms. This adaptability is crucial in the dynamic landscape of cybersecurity.

        6. Quick Response to Incidents:

        AI facilitates rapid response to security incidents by providing real-time analysis and alerts. This speed is essential in preventing or mitigating the impact of cyberattacks.

        Cons of AI in InfoSec:

        1. Sophistication of Attacks:

        As AI is integrated into cybersecurity defenses, attackers may also leverage AI to create more sophisticated and adaptive threats, leading to a continuous escalation in the complexity of cyberattacks.

        2. Ethical Concerns:

        The use of AI in cybersecurity raises ethical considerations, such as privacy issues, potential misuse of AI for surveillance, and the need for transparency in how AI systems operate.

        3. Cost and Resource Intensive:

        Implementing and maintaining AI-powered security systems can be resource-intensive, both in terms of financial investment and skilled personnel required for development, implementation, and ongoing management.

        4. False Positives and Negatives:

        AI systems are not infallible and may produce false positives (incorrectly flagging normal behavior as malicious) or false negatives (failing to detect actual threats). This poses challenges in maintaining a balance between security and user convenience.

        5. Lack of Human Understanding:

        AI lacks contextual understanding and human intuition, which may result in misinterpretation of certain situations or the inability to recognize subtle indicators of a potential threat. This is where QA and governance come in case something goes wrong.

        6. Dependency on Training Data:

        AI models rely on training data, and if the data used is biased or incomplete, it can lead to biased or inaccurate outcomes. Ensuring diverse and representative training data is crucial to the effectiveness of AI in InfoSec.

        About the author:

        Jeremy Swenson is a disruptive-thinking security entrepreneur, futurist / researcher, and senior management tech risk consultant. He is a frequent speaker, published writer, podcaster, and even does some pro bono consulting in these areas. He holds an MBA from St. Mary’s University of MN, an MSST (Master of Science in Security Technologies) degree from the University of Minnesota, and a BA in political science from the University of Wisconsin Eau Claire. He is an alum of the Federal Reserve Secure Payment Task Force, the Crystal, Robbinsdale and New Hope Citizens Police Academy, and the Minneapolis FBI Citizens Academy.

        Seven Cyber-Tech Observations of 2022 and What it Means for 2023.

        Minneapolis 01/17/23

        cryptonews #cyberrisk #techrisk #techinnovation #techyearinreview #ftxfraud #googlemandiant #infosec #musktwitter #twitterfiles #disinformation #cio #ciso #cto

        By Jeremy Swenson

        Summary:

        Fig. 1. 2022 Cyber Year in Review Mashup; Stock, 2023.

        The pandemic continues to be a big part of the catalyst for digital transformation in tech automation, identity and access management (IAM), big data, collaboration tools, artificial intelligence (AI), and increasingly the supply chain. Disinformation efforts morphed and grew last year with stronger crypto tie ins challenging data and culture; Twitter hype pump and dumps for example. Additionally, cryptocurrency-based money laundering, fraud, and Ponzi schemes increased partly due to weaknesses in the fintech ecosystem around compliance, coin splitting/mixing fog, and IAM complexity. This requires better blacklisting by crypto exchanges and banks to stop these illicit transactions erroring on the side of compliance, and it requires us to pay more attention to knowing and monitoring our own social media baselines.

        The Costa Rican Government was forced to declare a national emergency on 05/08/22 because the Conti Ransomware intrusion had extended to most of its governmental entities. This was a more advanced and persistent ransomware with Russian gang ties (Associated Press; NBC News, 06/17/22). This highlights the need for smaller countries to better partner with private infrastructure providers and to test for worst-case scenarios.

        We no longer have the same office due to mass work from home (WFH) and the mass resignation/gig economy. This infers increased automated zero-trust policies and tools for IAM with less physical badge access required. The security perimeter is now more defined by data analytics than physical/digital boundaries. Education and awareness around the review and removal of non-essential mobile apps grows as a top priority as mobile apps multiply. All the while, data breaches, and ransomware reach an all-time high while costing more to mitigate. Lastly, all these things make the Google acquisition of Mandiant more relevant and plausibly one of the most powerful security analytics and digital investigation entities in the world rivaling nation-state intelligence agencies.

        Intro:

        Every year I like to research and commentate on the most impactful security technology and business happenings from the prior year. This year is unique since crypto money laundering via splitting/mixing, disinformation, the pandemic, and mass resignation/gig economy continue to be a large part of the catalyst for most of these trends. All these trends are likely to significantly impact small businesses, government, education, high-tech, and large enterprise in big and small ways.

        1) The Main Purpose of Cryptocurrency Mixer and/or Splitter Services is Fraud and Money Laundering.

        Cryptocurrency mixer and/or splitter services serve no valid “real-world” ethical business use case considering the relevant fintech and legal options open. Even in the very rare case when you are a refugee fleeing a financially abusive government regime or a terrorist organization is seeking to steal your assets while the national currency is failing, like in Venezuela, which I wrote about in my 2014 article, “Thought$ On The Future of Digital Curren¢y For A Better World” – that is about political revolution and your personal safety more than anything else. Although cases like this give a valid reason why you might want to mix and/or split your crypto assets, that is not fully the same use case we’re talking about here with the recent uptick of ill-intended crypto mixer and/or splitter service use. Therefore, it’s only fair that we discuss the most likely and common use case, which is trending up, and not the few rare edge cases. This use case would be fraud, Ponzi schemes, and money laundering.

        The evidence does not support that a regular crypto exchange is the same thing as a mixer and/or splitter service. For definition’s sake, I am not defining mixing and/or splitting cryptocurrency as the same thing as selling, buying, or converting it – all of this can be done on one or more of the crypto exchanges which is why they are called exchanges. If they are the same or even considerably similar, then why are people and orgs using the mixer and/or splitter services at all? They use them because they offer a considerably different service. Using a mixer and/or splitter service assumes you have gotten some crypto beforehand, from a separate exchange – a step or more before in the daisy chain. This can be done via legal or illegal means. Moreover, why are people paying repeated and hugely excessive fees for these services? The fees are out of line with anything possibly comparable because there is higher compliance and legal risk for the operators of them in that they could get sanctioned like Blender-IO, FTX, Coinbase, Gemini, and others.

        You can still have privacy if that is what you are seeking via a semblance of legal moves such as a trust tied to a separate legal entity, family office entity, converting to real estate, and marriage entity – if you have time to do the paperwork. Legally savvy people have anonymity over their assets often to avoid fraudsters, sales reps, and just privacy for privacy’s sake – but again still not the same use case. Even when people/orgs use these legal instruments for privacy, they still have compliance reporting and tax obligations – some disclosure. Keep in mind some disclosure serves to protect you, that you in fact own the assets you say you own. Using these legal instruments with the right technical security including an encrypted VPN and multifactor authentication serves to sustain privacy, and you will then not need a crypto mixer and/or splitter.

        Yet if you had cryptocurrency and wanted strong privacy to protect your assets, why would you not at least use some of the aforementioned legal instruments or the like? Mostly because any attorney worth anything would be obligated to report this blatant suspected fraud, and would not want to tarnish their name on the filings, etc. Specifically, the attorney would have to see and know where and what entities the crypto was coming from and going to, under what contexts, and that could trigger them to report or refuse to work with them – a fraudster would want to avoid getting detected.

        Specifically, the use of multiple legal entities in different countries in a daisy chain of crypto coin mixing and/or splitting tends to be the pattern for persistent fraud and money laundering. That was the case in the $4.5-billion-dollar crypto theft out of NY (Crocodile of Wall Street), the Blender mixing fraud, and many other cases.

        A recent May 2022 U.S. Treasury press release concerning mixer service money laundering described it this way (Dept of Treasury; Press Release, 05/06/22):

        “Blended.io (Blender) is a virtual currency mixer that operates on the Bitcoin blockchain and indiscriminately facilitates illicit transactions by obfuscating their origin, destination, and counterparties. Blender receives a variety of transactions and mixes them together before transmitting them to their ultimate destinations. While the purported purpose is to increase privacy, mixers like Blender are commonly used by illicit actors. Blender has helped transfer more than $500 million worth of Bitcoin since its creation in 2017. Blender was used in the laundering process for DPRK’s Axie Infinity heist, processing over $20.5 million in illicit proceeds.”

        Fig 2. U.S. Treasury Dept; Blener.io Crypto Mixer Fraud, 2022.

        The question we as a society should be thinking about is tech ethics. What design feature crosses the line to enable fraud too much such that it is not pursued? For example, Silk Road crossed the line, selling illegal drugs, extortion, and other crime. Hacker networks cross the line when they breach companies and steal their credit card data and put it for sale on the dark web. Facebook crossed the line when it enabled bias and undue favor to impact policy outcomes.

        Crypto mixer and/or splitter services (not mere crypto exchanges) are about as close to “money laundering as a service” as it gets – relative to anything else technically available excluding the dark web where there are far worse things available technically. Obviously, the developers, product owners, and project managers behind the crypto mixer and/or splitter services like this are serving the fraud and money laundering use case more than anything else. Some semblance of the organized crime rings is very likely giving them money and direction to this end.

        If you are for and use mixer and/or splitter services then you run the risk of having your digital assets mixed with dirty digital assets, you have extortion high fees, you have zero customer service, no regulatory protection, no decedent Terms of Service and/or Privacy Policy if any, and you have no guarantee that it will even work the way you think it will.

        In fact, you have so much decentralized “so-called” privacy that it could work against you. For example, imagine you pay the high fees to mix and split your crypto multiple times, and then your crypto is stolen by one of the mixing and/or splitting services. This is likely because they know many of their customers are committing fraud and money laundering; yet even if they are not these platforms are associated with that. Therefore, if the platform operators steal their crypto in this process, the victims have little incentive to speak up. Moreover, the mixing and/or splitting service companies have a nice cover to steal it, privacy. They won’t admit that they stole it but will say something like “everything is private and so we can’t see or know but you are responsible for what private assets you have or don’t have”. They will say something like “stealing it is impossible” which of course is a complete lie.

        In sum, what reason do you have to trust a crypto mixing and/or splitting service with your digital assets as outlined above as they are hardly incentivized to protect them or you and operate in the shadows of antiquated non-western fintech regulation. So what really do you get besides likely fraud? What is the business rationale behind using these services as outlined above considering no solid argument or evidence can support it is privacy alone, and what net benefit do you get besides business-enabling money laundering and fraud?

        Now there are valid use cases for crypto and blockchain technology generally and here are five of them:

        1.      Innovative tech removing the central bank for peer-to-peer exchange that is faster and more global, especially helping the underbanked countries.

        2.      Smart contracts can be built on blockchain.

        3.      Blockchain can be used for crowdfunding.

        4.      Blockchain can be used for decentralized storage.

        5.      The traditional cash and coin supply chain is burdensomely wasteful, costly, dirty, and counterfeiting is a real issue. Why do you need to carry ten dollars in quarters or a wad of twenty-dollar bills or even have that be a nation’s economic backing in today’s tech world?

        Here are six tips to identify crypto-related scams:

        1.      With most businesses, it should be easy to find out who the key operators are. If you can’t find out who is running a cryptocurrency or exchange via LinkedIn, Medium, Twitter, a website, or the like be very cautious.

        2.      Whether in cash or cryptocurrency, any business opportunity promising free money is likely to be fake. If it sounds too good to be true it likely is. Multi-level marketing is one old example of this scam.

        3.      Never mix online dating and investment/financial advice. If you meet someone on a dating site or social media app, and then they want to show you how to invest in crypto or they ask you to send them crypto. No matter what sob story and huge return they are claiming it’s a scam (FTC).

        4.      Watch out for scammers who pretend to be celebrities who can multiply any cryptocurrency you send them. If you click on an unexpected link they send or send cryptocurrency to a so-called celebrity’s QR code, that money will go straight to a scammer, and it’ll be gone. Celebrities don’t have time to contact random people on social media, but they are easily impersonated (FTC).

        5.      Celebrities are however used to pump crypto prices via social media, so they get a windfall, and everyone else takes a hit. Watch out for crypto like Dogecoin which is heavily tied to celebrity pumps with no real-world business value. If you are lucky enough to get ahead, get out then.

        6.      Watch out for scammers who make big claims without details, white papers, filings, or explanations at all. No matter what the investment, find out how it works and ask questions about where your money is going. Honest investment managers or advisors want to share that information and will back it up with details in many documents and filings (FTC). 

        2) Disinformation Efforts Are Further Exposed:

        Disinformation has not slowed down any in 2022 due to sustained advancements in communications technologies, the growth of large social media networks, and the “appification” of everything thereby increasing the ease and capability of disinformation. Disinformation is defined as incorrect information intended to mislead or disrupt, especially propaganda issued by a government organization to a rival power or the media. For example, governments creating digital hate mobs to smear key activists or journalists, suppress dissent, undermine political opponents, spread lies, and control public opinion (Shelly Banjo; Bloomberg, 05/18/2019).

        Today’s disinformation war is largely digital via platforms like Facebook, Twitter, Instagram, Reddit, WhatsApp, Yelp, Tik-tok, SMS text messages, and many other lesser-known apps. Yet even state-sponsored and private news organizations are increasingly the weapon of choice, creating a false sense of validity. Undeniably, the battlefield is wherever many followers reside. 

        Bots and botnets are often behind the spread of disinformation, complicating efforts to trace and stop it. Further complicating this phenomenon is the number of app-to-app permissions. For example, the CNN and Twitter apps having permission to post to Facebook and then Facebook having permission to post to WordPress and then WordPress posting to Reddit, or any combination like this. Not only does this make it hard to identify the chain of custody and original source, but it also weakens privacy and security due to the many authentication permissions involved. The copied data is duplicated at each of these layers, which is an additional consideration.

        We all know that false news spreads faster than real news most of the time, largely because it is sensationalized. Since most disinformation draws in viewers which drives clicks and ad revenues; it is a money-making machine. If you can significantly control what’s trending in the news and/or social media, it impacts how many people will believe it. This in turn impacts how many people will act on that belief, good or bad. This is exacerbated when combined with human bias or irrational emotion.

        In 2022 there were many cases of fake crypto initial coin offerings (ICOs) and related scams including the Titanium Blockchain where investors lost at least $21 million (Dept of Justice; Press Release, 07/25/22). The Celsius’ crypto lending platform also came tumbling down largely because it was a social media-hyped Ponzi scheme (CNBC; Arjun Kharpal, 07/08/22). This negatively impacts culture by setting a misguided example of what is acceptable.

        Elon Musk’s controversial purchase of Twitter for $44 billion in October 2022 resulted in a big management shakeup and strategy change (New York Times; Kate Conger and Lauren Hirsch, 10/27/22). The goal was to reduce bias and misinformation in the name of free and fair speech. To this end, the new Twitter under Musk’s direction produced “The Twitter Files” which are a set of internal Twitter, Inc documents made public beginning in December 2022. This was done with the help of independent journalists Matt Taibbi, Bari Weiss, Lee Fang, and authors Michael Shellenberger, David Zweig and Alex Berenson.

        The sixth release of the Twitter Files was on 12/12/22 and revealed (Real Clear Politics; Kalev Leetaru, 12/20/22):

        “Twitter granted great deference to government agencies and select outside organizations. While any Twitter user can report a tweet for removal, officials at the platform provided more direct and expedited channels for select organizations, raising obvious ethical questions about the government’s non-public efforts at censorship. It also captured the degree to which law enforcement requested information – from the physical location of users to foreign influence – from social platforms outside of formal court orders, raising important questions of due process and accountability.”

        Fig. 3. Elon Musk Twitter Freedom of Speech Mash Up; Stock / Getty, 2022.

        With the help of Twitter’s misinformation, huge swaths of confused voters and activists aligned more with speculation and emotion/hype than unbiased facts, and/or project themselves as fake commentators. This dirtied the data in terms of the election process and only begs the question – which parts of the election information process are broken? This normalizes petty policy fights, emotional reasoning, lack of unbiased intellectualism – negatively impacting western culture. All to the threat actor’s delight. Increased public-to-private partnerships, more educational rigor, and enhanced privacy protections for election and voter data are needed to combat this disinformation.

        3) Identity and Access Management (IAM) Scrutiny Drives Zero Trust Orchestration:

        The pandemic and mass resignation/gig economy has pushed most organizations to amass work from home (WFH) posture. Generally, this improves productivity making it likely to become the new norm. Albeit with new rules and controls. To support this, 51% of business leaders started speeding up the deployment of zero trust capabilities in 2020 (Andrew Conway; Microsoft, 08/19/20) and there is no evidence to suggest this is slowing down in 2022 but rather it is likely increasing to support zero trust orchestration.

        Orchestration is enhanced automation between partner zero trust applications and data, while leaving next to no blind spots. This reduces risk and increases visibility and infrastructure control in an agile way. The quantified benefit of deploying mature zero trust capabilities including orchestration is on average $ 1.51 million dollars less in breach response costs when compared to an organization who has not rolled out zero trust capabilities (IBM Security; Cost of A Data Breach Report, 2022). 

        Fig. 4. Zero Trust Components to Orchestration; Microsoft, 09/17/21

        Zero trust moves organizations to a need-to-know-only access mindset with inherent deny rules, all the while assuming you are compromised. This infers single sign-on at the personal device level and improved multifactor authentication. It also infers better role-based access controls (RBAC), firewalled networks, improved need-to-know policies, effective whitelisting and blacking listing of apps, group membership reviews, and state of the art privileged access management (PAM) tools for the next year. In the future more of this is likely to better automate and orchestrate (Fig. 4.) zero trust abilities so that one part does not hinder another part via complexity fog.

        4) Security Perimeter is Now More Defined by Data Analytics than Physical/Digital Boundaries:

        This increased WFH posture blurs the security perimeter physically and digitally. New IP addresses, internet volume, routing, geolocation, and virtual machines (VMs) exacerbate this blur. This raises the criticality of good data analytics and dashboarding to define the digital boundaries in real time. Therefore, prior audits, security controls, and policies may be ineffective. For instance, empty corporate offices are the physical byproduct of mass WFH, requiring organizations to set default disable for badge access. Extra security in or near server rooms is also required. The pandemic has also made vendor interactions more digital, so digital vendor connection points should be reduced and monitored in real time, and the related exception policies should be re-evaluated.

        New data lakes and machine learning informed patterns can better define security perimeter baselines. One example of this includes knowing what percent of your remote workforce is on what internet providers and what type? For example, Google fiber, Comcast cable, CenturyLink DSL, ATT 5G, etc. There are only certain modems that can go with each of these networks and that leaves a data trail. Of course, it could be any type of router. What type of device do they connect with MAC, Apple, VM, or other, and if it is healthy – all can be determined in relation to security perimeter analytics.

        5) Cyber Firm Mandiant Was Purchased by Google Spawning Private Sector Security Innovation.

        Google completed its acquisition of security and incident response firm Mandiant for $5.4 billion dollars in Sept 2022 (Google Cloud; Thomas Kurian CEO – Google Cloud, 09/12/22). This acquisition positions the search and advertising leader with better cloud security infrastructure, better market appeal, and more diversification. With a more advanced and integrated security foundation, Google Cloud can compete better against market leader Amazon Web Services (AWS) and runner-up Microsoft Azure. They will do this on more than price because features will likely grow to leverage their differentiating machine learning and analytical abilities via clients throughout the industry.

        Other benefits of integrating Mandiant include improved automated breach response logic. This is because security teams can now gather the required data and then share it across Google customers to help analyze ransomware threat variants. Many of Google’s security related products will also be enhanced by Mandiant’s threat intelligence and incident response capabilities. Some of these products include Google’s security orchestration, automation and response (SOAR) tool which is described this way, “Part of Chronicle Security Operations, Chronicle SOAR enables modern, fast and effective response to cyber threats by combining playbook automation, case management and integrated threat intelligence in one cloud-native, intuitive experience” (Google; Google Cloud, 01/16/23).

        According to Dave Cundiff, CISO at Cyvatar, “if Google, as one of the leaders in data science, can progress and move forward the ability to prevent the unknown vectors of attack before they happen based upon the mountains of data available from previous breaches investigated by Mandiant, there could truly be a significant advancement in cybersecurity for its cloud customers” (SC Media; Steve Zurier, 04/15/22). This results in a strong focus on prevention vs. response, which is greatly needed. Lastly, since AWS and Microsoft will be unlikely to hire Mandiant directly because Google owns them, they will likely look to acquire another security services player soon.

        6) Data Breaches Have Increased in Number and Cost but Are Generally Identified Faster.

        The pandemic has continued to be a part of the catalyst for increased lawlessness including fraud, ransomware, data theft, and other types of profitable hacking. Cybercriminals are more aggressively taking advantage of geopolitical conflict and legal standing gaps. For example, almost all hacking operations are in countries that do not have friendly geopolitical relations with the United States or its allies – and all their many proxy hops would stay consistent with this. These proxy hops are how they hide their true location and identity.

        Moreover, with local police departments extremely overworked and understaffed with their number one priority being responding to the huge uptick in violent crime in most major cities, white-collar cybercrimes remain a low priority. Additionally, local police departments have few cyber response capabilities depending on the size of their precinct. Often, they must sheepishly defer to the FBI, CISA, and the Secret Service, or their delegates for help. Yet not unsurprisingly, there is a backlog for that as well with preference going to large companies of national concern that fall clearly into one of the 16 critical infrastructures. That is if turf fights and bureaucratic roadblocks don’t make things worse. Thus, many mid and small-sized businesses are left in the cold to fend for themselves which often results in them paying ransomware, and then being a victim a second time all the while their insurance carrier denes their claims, raises their rate, and/or drops them.

        Further complicating this is lack of clarity on data breach and business interruption insurance coverage and terms. Keep in mind most general business liability insurance policies and terms were drafted before hacking was invented so they are by default behind the technology. Most often general liability business insurance covers bodily injuries and property damage resulting from your products, services, or operations. Please see my related article “10 Things IT Executives Must Know About Cyber Insurance” to understand incident response and to reduce the risk of inadequate coverage and/or claims denials.

        Data breaches are more expensive than ever. IBM’s 2022 Annual Cost of a Date Breach Report revealed increased costs associated with the average data breach at an estimated $4.35 million per organization. This is a $110,000 year-over-year increase at 2.6% and the highest in the reports history (Fig. 5). However, the average time to identify and contain a data breach decreased both decreased by 5 days (Fig 6). This is a total decrease of 10 days or 3.5%. Yet this is for general data breaches and not ransomware attacks.

        Fig 5. Cost of A Data Breach Increases 2021 to 2022 (IBM Security, 2022).
        Fig. 6. Average Time To Identify and Contain a Data Breaches Decreases 2021 to 2022, (IBM Security, 2022).

        Lastly, this is a lot of money for an organization to spend on a breach. Yet this amount could be higher when you factor in other long-term consequence costs such as increased risk of a second breach, brand damage, and/or delayed regulatory penalties that were below the surface – all of which differs by industry. In sum, it is cheaper and more risk prudent to spend even $4.35 million or a relative percentage at your organization on preventative zero trust capabilities than to deal with the cluster of a data breach.

        7) The Costa Rican Government was Heavily Hacked and Encrypted by the Conti Ransomware.

        The Costa Rican Government was forced to declare a national emergency on 05/08/22 because the Conti Ransomware intrusion had extended to most of its governmental entities. Conti is an advanced and persistent ransomware as a service attack platform. The attackers are believed to the Russian cybercrime gang Wizard Spider (Associated Press; NBC News, 06/17/22). “The threat actor entry point was a system belonging to Costa Rica’s Ministry of Finance, to which a member of the group referred to as ‘MemberX’ gained access over a VPN connection using compromised credentials” (Bleeping Computer; Ionut Ilascu, 07/21/22). Phishing is a common way to get in to monitor for said credentials but in this case it was done “Using the Mimikatz post-exploitation tool for exfiltrating credentials, the adversary collected the logon passwords and NTDS hashes for the local users, thus getting “plaintext and bruteable local admin, domain and enterprise administrator hashes” (Bleeping Computer; Ionut Ilascu, 07/21/22).

        Fig. 7. Costa Rica Conti Ransomware Attack Architecture; AdvIntel via (Bleeping Computer; Ionut Ilascu, 07/21/22).

        This resulted in 672GB of data leaked and dumped or 97% of what was stolen (Bleeping Computer; Ionut Ilascu, 07/21/22). Some believe Costa Rica was targeted because they supported Ukraine against Russia. This highlights the need for smaller countries to better partner with private infrastructure providers and to test for worst-case scenarios.

        Take-Aways:

        The pandemic remains a catalyst for digital transformation in tech automation, IAM, big data, collaboration tools, and AI. We no longer have the same office and thus less badge access is needed. The growth and acceptability of mass WFH combined with the mass resignation/gig economy remind employers that great pay and culture alone are not enough to keep top talent. Signing bonuses and personalized treatment are likely needed. Single sign-on (SSO) will expand to personal devices and smartphones/watches. Geolocation-based authentication is here to stay with double biometrics likely. The security perimeter is now more defined by data analytics than physical/digital boundaries, and we should dashboard this with machine learning and AI tools.

        Education and awareness around the review and removal of non-essential mobile apps is a top priority. Especially for mobile devices used separately or jointly for work purposes. This requires a better understanding of geolocation, QR code scanning, couponing, digital signage, in-text ads, micropayments, Bluetooth, geofencing, e-readers, HTML5, etc. A bring your own device (BYOD) policy needs to be written, followed, and updated often informed by need-to-know and role-based access (RBAC) principles. Organizations should consider forming a mobile ecosystem security committee to make sure this unique risk is not overlooked or overly merged with traditional web/IT risk. Mapping the mobile ecosystem components in detail is a must.

        IT and security professionals need to realize that alleviating disinformation is about security before politics. We should not be afraid to talk about it because if we are then our organizations will stay weak and insecure and we will be plied by the same political bias that we fear confronting. As security professionals, we are patriots and defenders of wherever we live and work. We need to know what our social media baseline is across platforms. More social media training is needed as many security professionals still think it is mostly an external marketing thing. Public-to-private partnerships need to improve and app to app permissions need to be scrutinized. Enhanced privacy protections for election and voter data are needed. Everyone does not need to be a journalist, but everyone can have the common sense to identify malware-inspired fake news. We must report undue bias in big tech from an IT, compliance, media, and a security perspective.

        Cloud infra will continue to grow fast creating perimeter and compliance complexity/fog. Organizations should preconfigure cloud-scale options and spend more on cloud-trained staff. They should also make sure that they are selecting more than two or three cloud providers, all separate from one another. This helps staff get cross-trained on different cloud platforms and add-ons. It also mitigates risk and makes vendors bid more competitively. 

        In regard to cryptocurrency, NFTs, ICOs, and related exchanges – watch out for scammers who make big claims without details, white papers, filings, or explanations at all. No matter what the investment, find out how it works and ask questions about where your money is going. Honest investment managers or advisors want to share that information and will back it up with details in many documents and filings (FTC).

        Moreover, better blacklisting by crypto exchanges and banks is needed to stop these illicit transactions erroring on the side of compliance, and it requires us to pay more attention to knowing and monitoring our own social media baselines. If you are for and use crypto mixer and/or splitter services then you run the risk of having your digital assets mixed with dirty digital assets, you have extortion high fees, you have zero customer service, no regulatory protection, no decent Terms of Service and/or Privacy Policy if any, and you have no guarantee that it will even work the way you think it will.

        About the Author:

        Jeremy Swenson is a disruptive-thinking security entrepreneur, futurist/researcher, and senior management tech risk consultant. Over 17 years he has held progressive roles at many banks, insurance companies, retailers, healthcare orgs, and even governments including being a member of the Federal Reserve Secure Payment Task Force. Organizations relish in his ability to bridge gaps and flesh out hidden risk management solutions while at the same time improving processes. He is a frequent speaker, published writer, podcaster, and even does some pro bono consulting in these areas. As a futurist, his writings on digital currency, the Target data breach, and Google combining Google + video chat with Google Hangouts video chat have been validated by many. He holds an MBA from St. Mary’s University of MN, an MSST (Master of Science in Security Technologies) degree from the University of Minnesota, and a BA in political science from the University of Wisconsin Eau Claire.

        The Main Purpose of Cryptocurrency Mixer and/or Splitter Services is Fraud and Money Laundering.

        Cryptocurrency mixer and/or splitter services serve no valid “real-world” ethical business use case considering the relevant FinTech and legal options open. Even in the very rare case when you are a refugee fleeing a financially abusive government regime or terrorist organization is seeking to steal your assets while the national currency is failing, like in Venezuela which I wrote about in my 2014 article; that is about political revolution and your personal safety more than anything else. Although cases like this give a valid reason why you might want to mix and/or split your crypto assets – that’s not fully the same use case we’re talking about here with the recent uptick of crypto mixer and/or splitter service use. It’s only fair that we discuss the most likely and common use case, which is trending up, and not the few rare edge cases. This use case would be fraud and money laundering.

        The evidence does not support that a regular crypto exchange is the same thing as a mixer and/or splitter service. For definitions sake, I am not defining mixing and/or splitting cryptocurrency as the same thing as selling, buying, or converting it – all of this can be done on one or more of the crypto exchanges which is why they are called exchanges. If they are the same or even considerably similar, then why are people and orgs using the mixer and/or splitter services at all? They use them because they offer a considerably different service. Using a mixer and/or splitter services assumes you have gotten some crypto beforehand, from a separate exchange, a step or more before in the daisy chain. This can be done via legal or illegal means. Moreover, why are they paying repeated and hugely excessive fees for these services? The fees are out of line with anything possibly comparable because there is higher compliance and legal risk for the operators of them in that they could get sanctioned like Blender.IO and others.

        You can still have privacy if that is what you are seeking via a semblance of legal moves such as a trust tied to a separate legal entity, family office entity, converting to real estate, and marriage entity – if you have time to do the paperwork. Legally savvy people have anonymity over their assets often to avoid fraudsters, sales reps, and just privacy for privacy’s sake – but again still not the same use case. Even when people/orgs use these legal instruments for privacy, they still have compliance reporting and tax obligations – I.E., some disclosure. Keep in mind some disclosure serves to protect you that you in fact own the assets you say you own. Using these legal instruments with the right technical security including an encrypted VPN and multifactor authentication serves to sustain privacy, and you will then not need a crypto mixer and/or splitter.

        Yet if you had cryptocurrency and wanted strong privacy to protect your assets, why would you not at least use some of the aforementioned legal instruments or the like? Mostly because any attorney worth anything would be obligated to report this blatant suspected fraud, and would not want to tarnish their name on the filings, etc. Specifically, the attorney would have to see and know where and what entities the crypto was coming from and going to, under what contexts, and that could trigger them to report or refuse to work with them – I.E. a fraudster would want to avoid getting detected.

        Specifically, the use of multiple legal entities in different countries in a daisy chain of crypto coin mixing and/or splitting tends to be the pattern for persistent fraud and money laundering. That was the case in the $4.5-billion-dollar crypto theft out of NY and in Blender mixing fraud, and many other cases.

        A recent U.S. Treasury press release concerning mixer service money laundering described it this way:

        • “Blended.io (Blender) is a virtual currency mixer that operates on the Bitcoin blockchain and indiscriminately facilitates illicit transactions by obfuscating their origin, destination, and counterparties. Blender receives a variety of transactions and mixes them together before transmitting them to their ultimate destinations. While the purported purpose is to increase privacy, mixers like Blender are commonly used by illicit actors. Blender has helped transfer more than $500 million worth of Bitcoin since its creation in 2017. Blender was used in the laundering process for DPRK’s Axie Infinity heist, processing over $20.5 million in illicit proceeds”.
        Fig 1. U.S. Treasury Dept, Blener.io Crypto Mixer Fraud, 2022.

        The question we as a society should be thinking about is tech ethics. What design feature crosses the line to enable fraud too much such that it is not pursued? For example, Silk Road crossed the line, selling illegal drugs, extortion, and other crime. Hacker networks cross the line when they breach companies and steal their credit card data and put it for sale on the dark web. Facebook crossed the line when it enabled bias and undue favor to impact policy outcomes.

        Crypto mixer and/or splitter services (not mere crypto exchanges) are about as close to “money laundering as a service” as it gets – relative to anything else technically available excluding the dark web where there are far worse things available technically. Obviously, the developers, product owners, and project managers behind the crypto mixer and/or splitter services like this are serving the fraud and money laundering use case more than anything else. Some semblance of the organized crime rings is very likely giving them money and direction to this end.

        If you are for and use mixer and/or splitter services then you run the risk of having your digital assets mixed with dirty digital assets, you have extortion high fees, you have zero customer service, no regulatory protection, no decedent Terms of Service and/or Privacy Policy if any, and you have no guarantee that it will even work the way you think it will.

        In fact, you have so much decentralized “so-called” privacy that it could work against you. For example, imagine you pay the high fees to mix and split your crypto multiple times, and then your crypto is stolen by one of the mixing and/or splitting services. This is likely because they know many of their customers are committing fraud and money laundering, yet even if they are not these platforms are associated with that. Therefore, if the platform operators steal their crypto in this process, the victims have little incentive to speak up. Moreover, the mixing and/or splitting service companies have a nice cover to steal it, privacy. They won’t admit that they stole it but will say something like “everything is private and so we can’t see or know but you are responsible for what private assets you have or don’t have”. They will say something like “stealing it is impossible” which is course is a complete lie.

        In sum, what reason do you have to trust a crypto mixing and/or splitting service with your digital assets as outlined above as they are hardly incentivized to protect them or you and operate in the shadows of antiquated non-western fintech regulation. So, what really do you get besides likely fraud? What is the business rationale behind using these services as outlined above considering no solid argument or evidence can support it is privacy alone, and what net benefit do you get besides business-enabling money laundering and fraud?

        Now there are valid use cases for crypto and blockchain generally and here are five of them:

        1. Innovative tech removing the central bank for peer-to-peer exchange that is faster and more global, especially helping the underbanked countries.
        2. Smart contracts can be built on blockchain.
        3. Blockchain can be used for crowdfunding.
        4. Blockchain can be used for decentralized storage.
        5. The traditional cash and coin supply chain is burdensomely wasteful, costly, dirty, and counterfeiting is a real issue. Why do you need to carry ten dollars in quarters or a wad of twenty-dollar bills or even have that be a nation’s economic backing in today’s tech world?

        Here are six tips to identify crypto-related scams:

        1. With most businesses, it should be easy to find out who the key operators are. If you can’t find out who is running a cryptocurrency or exchange via LinkedIn, Medium, Twitter, a website, or the like be very cautious.
        2. Whether in cash or cryptocurrency, any business opportunity promising free money is likely to be fake. If it sounds too good to be true it likely is. Multi-level marketing is one old example of this scam.
        3. Never mix online dating and investment/financial advice. If you meet someone on a dating site or social media app, and then they want to show you how to invest in crypto or they ask you to send them crypto. No matter what sob story and huge return they are claiming it’s a scam (FTC).
        4. Watch out for scammers who pretend to be celebrities who can multiply any cryptocurrency you send them. If you click on an unexpected link they send or send cryptocurrency to a so-called celebrity’s QR code, that money will go straight to a scammer, and it’ll be gone. Celebrities don’t have time to contact random people on social media, but they are easily impersonated (FTC).
        5. Celebrities are however used to pump crypto prices via social media, so they get a windfall, and everyone else takes a hit. Watch out for crypto like Dogecoin which is heavily tied to celebrity pumps with no real-world business value. If you are lucky enough to get ahead, get out then.
        6. Watch out for scammers who make big claims without details, white papers, filings, or explanations at all. No matter what the investment, find out how it works and ask questions about where your money is going. Honest investment managers or advisors want to share that information and will back it up with details in many documents and filings (FTC).

        Jeremy Swenson is a disruptive thinking security entrepreneur, futurist/researcher, and senior management tech risk consultant. Over 17 years he has held progressive roles at many banks, insurance companies, retailers, healthcare orgs, and even governments including being a member of the Federal Reserve Secure Payment Task Force. Organizations relish in his ability to bridge gaps and flesh out hidden risk management solutions while at the same time improving processes. He is a frequent speaker, published writer, podcaster, and even does some pro bono consulting in these areas. As a futurist, his writings on digital currency, the Target data breach, and Google combining Google + video chat with Google Hangouts video chat have been validated by many. He holds an MBA from St. Mary’s University of MN, a MSST (Master of Science in Security Technologies) degree from the University of Minnesota, and a BA in political science from the University of Wisconsin Eau Claire.

        Five Cyber-Tech Trends of 2021 and What it Means for 2022.

        Minneapolis 01/08/22

        By Jeremy Swenson

        Intro:

        Every year I like to research and commentate on the most impactful security technology and business happenings from the prior year. This year is unique since the pandemic and mass resignation/gig economy continues to be a large part of the catalyst for most of these trends. All these trends are likely to significantly impact small businesses, government, education, high tech, and large enterprise in big and small ways.

        Fig. 1. Facebook Whistle Blower and Disinformation Mashup (Getty & Stock Mashup, 2021).

        Summary:

        The pandemic continues to be a big part of the catalyst for digital transformation in tech automation, identity and access management (IAM), big data, collaboration tools, artificial intelligence (AI), and increasingly the supply chain. Disinformation efforts morphed and grew last year challenging data and culture. This requires us to put more attention on knowing and monitoring our own social media baselines. We no longer have the same office due to mass work from home (WFH) and the mass resignation/gig economy. This infers increased automated zero-trust policies and tools for IAM with less physical badge access required. The security perimeter is now more defined by data analytics than physical/digital boundaries.

        The importance of supply chain cyber security was elevated by the Biden Administration’s Executive Order 1407 in response to hacks including SolarWinds and Colonial Pipeline. Education and awareness around the review and removal of non-essential mobile apps grows as a top priority as mobile apps multiply. All the while, data breaches, and ransomware reach an all-time high while costing more to mitigate.

        1) Disinformation Efforts Accelerate Challenging Data and Culture:

        Disinformation has not slowed down any in 2021 due to sustained advancements in communications technologies, the growth of large social media networks, and the “appification” of everything thereby increasing the ease and capability of disinformation. Disinformation is defined as incorrect information intended to mislead or disrupt, especially propaganda issued by a government organization to a rival power or the media. For example, governments creating digital hate mobs to smear key activists or journalists, suppress dissent, undermine political opponents, spread lies, and control public opinion (Shelly Banjo; Bloomberg, 05/18/2019).

        Today’s disinformation war is largely digital via platforms like Facebook, Twitter, Instagram, Reddit, WhatsApp, Yelp, Tik-tok, SMS text messages, and many other lesser-known apps. Yet even state-sponsored and private news organizations are increasingly the weapon of choice, creating a false sense of validity. Undeniably, the battlefield is wherever many followers reside. 

        Bots and botnets are often behind the spread of disinformation, complicating efforts to trace and stop it. Further complicating this phenomenon is the number of app-to-app permissions. For example, the CNN and Twitter apps having permission to post to Facebook and then Facebook having permission to post to WordPress and then WordPress posting to Reddit, or any combination like this. Not only does this make it hard to identify the chain of custody and original source, but it also weakens privacy and security due to the many authentication permissions involved. The copied data is duplicated at each of these layers which is an additional consideration.

        We all know that false news spreads faster than real news most of the time, largely because it is sensationalized. Since most disinformation draws in viewers which drives clicks and ad revenues; it is a money-making machine. If you can significantly control what’s trending in the news and/or social media, it impacts how many people will believe it. This in turn impacts how many people will act on that belief, good or bad. This is exacerbated when combined with human bias or irrational emotion. For example, in late 2021 there were many cases of fake COVID-19 vaccines being offered in response to human fear (FDA; 09/28/2021). This negatively impacts culture by setting a misguided example of what is acceptable.

        There were several widely reported cases of political disinformation in 2021 including misleading texts, e-mails, mailers, Facebook censorship, and robocalls designed to confuse American voters amid the already stressful pandemic. Like a narcissist’s triangulation trap, these disinformation bursts riled political opponents on both sides in all states creating miscommunication, ad hominin attacks, and even derailed careers with impacts into the future (PBS; The Hinkley Report, 11/24/20 and Daniel Funke; USA Today, 12/23/21).

        Facebook is significantly involved in disinformation as one recent study stated, “Globally, Facebook made the wrong decision for 83 percent of those ads that had not been declared as political by their advertisers and that Facebook or the researchers deemed political. Facebook both overcounted and undercounted political ads in this group” (New York University; Cybersecurity For Democracy, 2021). Of course, Facebook disinformation whistleblower Frances Haugen who testified before Congress in 2021 is only more evidence of these and related Facebook failings. Specifically that “Facebook executives, including CEO Mark Zuckerberg, misstated and omitted key details about what was known about Facebook and Instagram’s ability to cause harm” (Bobby Allyn; NPR, 10/05/21).

        Fig. 2. Facebook Gaps in Ad Transparency (IMEC-DistriNet KU Leuven and NYU Cyber Security for Democracy, 2021).

        With the help of Facebook’s misinformation, huge swaths of confused voters and activists aligned more with speculation and emotion/hype than unbiased facts, and/or project themselves as fake commentators. This dirtied the data in terms of the election process and only begs the question – which parts of the election information process are broken? This normalizes petty policy fights, emotional reasoning, lack of unbiased intellectualism – negatively impacting western culture. All to the threat actor’s delight. Increased public to private partnerships, more educational rigor, and enhanced privacy protections for election and voter data are needed to combat this disinformation.

        2) Identity and Access Management (IAM) Scrutiny Drives Zero Trust Orchestration:

        The pandemic and mass resignation/gig economy has pushed most organizations to amass work from home (WFH) posture. Generally, this improves productivity making it likely to become the new norm. Albeit with new rules and controls. To support this, 51% of business leaders started speeding up the deployment of zero trust capabilities in 2020 (Andrew Conway; Microsoft, 08/19/20) and there is no evidence to suggest this is slowing down in the next year but rather it is likely increasing to support zero trust orchestration. Orchestration is enhanced automation between partner zero trust applications and data, while leaving next to no blind spots. This reduces risk and increases visibility and infrastructure control in an agile way. The quantified benefit of deploying mature zero trust capabilities including orchestration is on average $ 1.76 million dollars less in breach response costs when compared to an organization who has not rolled out zero trust capabilities (IBM Security, Cost of A Data Breach Report, 2021). 

        Fig. 3. Zero Trust Components to Orchestration (Microsoft, 09/17/21).

        Zero trust moves organizations to a need-to-know-only access mindset with inherent deny rules, all the while assuming you are compromised. This infers single sign-on at the personal device level and improved multifactor authentication. It also infers better role-based access controls (RBAC), firewalled networks, improved need-to-know policies, effective whitelisting and blacking listing of apps, group membership reviews, and state of the art PAM (privileged access management) tools for the next year. In the future more of this is likely to better automate and orchestrate (Fig. 3.) zero trust abilities so that one part does not hinder another part via complexity fog.

        3) Security Perimeter is Now More Defined by Data Analytics than Physical/Digital Boundaries:

        This increased WFH posture blurs the security perimeter physically and digitally. New IP addresses, internet volume, routing, geolocation, and virtual machines (VMs) exacerbate this blur. This raises the criticality of good data analytics and dashboarding to define the digital boundaries in real-time. Therefore, prior audits, security controls, and policies may be ineffective. For instance, empty corporate offices are the physical byproduct of mass WFH, requiring organizations to set default disable for badge access. Extra security in or near server rooms is also required. The pandemic has also made vendor interactions more digital, so digital vendor connection points should be reduced and monitored in real-time, and the related exception policies should be re-evaluated.

        New data lakes and machine learning informed patterns can better define security perimeter baselines. One example of this includes knowing what percent of your remote workforce is on what internet providers and what type? For example, Google fiber, Comcast cable, CenturyLink DSL, ATT 5G, etc. There are only certain modems that can go with each of these networks and that leaves a data trail. Of course, it could be any type of router. What type of device do they connect with MAC, Apple, VM, or other, and if it is healthy can all be determined in relationship to security perimeter analytics.

        4) Supply Chain Risk and Attacks Increase Prompting Government Action:

        Every organization has a supply chain big or small. There are even subcomponents of the supply chain that can be hard to see like third/fourth-party vendors. A supply chain attack works by targeting a third/fourth party with access to an organization’s systems instead of hacking their networks directly.

        In 2021 cybercriminals focused their surveillance on key components of the supply chain including hacking DNS servers, switches, routers, VPN concentrators and services, and other supply chain connected components at the vendor level. Of note was the massive Colonial Gas Pipeline hack that spiked fuel prices this last summer. This was caused by one compromised VPN account informed by a leaked password from the dark web (Turton, William; and Mehrotra, Kartikay; Bloomberg, 06/04/21). The SolarWinds hack was another supply chain-originated attack in that they got into SolarWinds IT management product Orien which in turn got them into the networks of most of the customers of that product (Lily Hay Newman; Wired, 12/19/21). The research consensus unsurprisingly ties this attack to Russian affiliated threat actors and there is no evidence contracting that.

        In response to these and related attacks the U.S. Presidential Administration issued Executive Order 14017, the heart of which requires those who manufacture and distribute software a new awareness of their supply chain to include what is in their products, even open-source software (White House; 05/12/21). This in addition to more spending on CISA hiring and public relations efforts for vulnerabilities and NIST framework conformance. Time will tell what this order delivers as it is dependent on what private sector players do.

        Fig. 4. Supply Chain Cyber Attack Diagram (INSURETrust, 2021).

        5) Data Breaches Have Greatly Increased in Number and Cost:

        The pandemic has continued to be a part of the catalyst for increased lawlessness including fraud, ransomware, data theft, and other types of profitable hacking. Cybercriminals are more aggressively taking advantage of geopolitical conflict and legal standing gaps. For example, almost all hacking operations are in countries that do not have friendly geopolitical relations with the United States or its allies – and all their many proxy hops would stay consistent with this. These proxy hops are how they hide their true location and identity.

        Moreover, with local police departments extremely overworked and understaffed with their number one priority being responding to the huge uptick in violent crime in most major cities, white-collar cybercrimes remain a low priority. Additionally, local police departments have few cyber response capabilities depending on the size of their precinct. Often, they must sheepishly defer to the FBI, CISA, and the Secret Service, or their delegates for help. Yet not unsurprisingly, there is a backlog for that as well with preference going to large companies of national concern that fall clearly into one of the 16 critical infrastructures. That is if turf fights and bureaucratic roadblocks don’t make things worse. Thus, many mid and small-sized businesses are left in the cold to fend for themselves which often results in them paying ransomware, and then being a victim a second time all the while their insurance carrier drops them.

        Further complicating this is lack of clarity on data breach and business interruption insurance coverage and terms. Keep in mind most general business liability insurance policies and terms were drafted before hacking was invented so they are by default behind the technology. Most often general liability business insurance covers bodily injuries and property damage resulting from your products, services, or operations. Please see my related article 10 Things IT Executives Must Know About Cyber Insurance to understand incident response and to reduce the risk of inadequate coverage and/or claims denials.

        According to the Identity Theft Resource Center (ITRC)’s 2021Q3 Data Breach Report, there was a 17% year-over increase as of 09/30/21. This means that by the time they finish their Q4 2021 report it’s likely to be above a 30% year-over-year increase. Breaches are also more costly for organizations suffering them according to the IBM Security Cost of Data Breach Report (Fig 5).

        Fig 5. Cost of A Data Breach Increases 2020 to 2021 (IBM Security, 2021).

        From 2020 to 2021 the average cost of a data breach in U.S. dollars rose to $4.24 million from $3.86 million. This is almost a 10% increase at 9.1%. In contrast, the preceding 4 years were relatively flat (Fig 5). The pandemic and policing conundrum is a considerable part of this uptick.

        Lastly, this is a lot of money for an organization to spend on a breach. Yet this amount could be higher when you factor in other long-term consequence costs such as increased risk of a second breach, brand damage, and/or delayed regulatory penalties that were below the surface – all of which differs by industry. In sum, it is cheaper and more risk prudent to spend even $4.24 million or a relative percentage at your organization on preventative zero trust capabilities than to deal with the cluster of a data breach.

        Take-Aways:

        COVID-19 remains a catalyst for digital transformation in tech automation, IAM, big data, collaboration tools, and AI. We no longer have the same office and thus less badge access is needed. The growth and acceptability of mass WFH combined with the mass resignation/gig economy remind employers that great pay and culture alone are not enough to keep top talent. Signing bonuses and personalized treatment are likely needed. Single sign-on (SSO) will expand to personal devices and smartphones/watches. Geolocation-based authentication is here to stay with double biometrics likely. The security perimeter is now more defined by data analytics than physical/digital boundaries, and we should dashboard this with machine learning and AI tools.

        Education and awareness around the review and removal of non-essential mobile apps is a top priority. Especially for mobile devices used separately or jointly for work purposes. This requires a better understanding of geolocation, QR code scanning, couponing, digital signage, in-text ads, micropayments, Bluetooth, geofencing, e-readers, HTML5, etc. A bring your own device (BYOD) policy needs to be written, followed, and updated often informed by need-to-know and role-based access (RBAC) principles. Organizations should consider forming a mobile ecosystem security committee to make sure this unique risk is not overlooked or overly merged with traditional web/IT risk. Mapping the mobile ecosystem components in detail is a must.

        IT and security professionals need to realize that alleviating disinformation is about security before politics. We should not be afraid to talk about it because if we are then our organizations will stay weak and insecure and we will be plied by the same political bias that we fear confronting. As security professionals, we are patriots and defenders of wherever we live and work. We need to know what our social media baseline is across platforms. More social media training is needed as many security professionals still think it is mostly an external marketing thing. Public-to-private partnerships need to improve and app to app permissions need to be scrutinized. Enhanced privacy protections for election and voter data are needed. Everyone does not need to be a journalist, but everyone can have the common sense to identify malware-inspired fake news. We must report undue bias in big tech from an IT, compliance, media, and a security perspective.

        Cloud infra will continue to grow fast creating perimeter and compliance complexity/fog. Organizations should preconfigure cloud-scale options and spend more on cloud-trained staff. They should also make sure that they are selecting more than two or three cloud providers, all separate from one another. This helps staff get cross-trained on different cloud platforms and add-ons. It also mitigates risk and makes vendors bid more competitively. 

        The increase in number and cost of data breaches was in part attributed to vulnerabilities in supply chains in a few national data breach incidents in 2021. Part of this was addressed in President Biden’s Executive Order 1407 on supply chain security. This reminds us to replace outdated routers, switches, repeaters, controllers, and to patch them immediately. It also reminds us to separate and limit network vendor access points to strictly what is needed and for a limited time window. Last but not least, we must have up-to-date thorough business interruption / cyber insurance with detailed knowledge of what it requires for incident response with breach vendors pre-selected.  

        About the Author:

        Jeremy Swenson is a disruptive thinking security entrepreneur, futurist/researcher, and senior management tech risk consultant. Over 17 years he has held progressive roles at many banks, insurance companies, retailers, healthcare orgs, and even governments including being a member of the Federal Reserve Secure Payment Task Force. Organizations relish in his ability to bridge gaps and flesh out hidden risk management solutions while at the same time improving processes. He is a frequent speaker, published writer, podcaster, and even does some pro bono consulting in these areas. As a futurist, his writings on digital currency, the Target data breach, and Google combining Google + video chat with Google Hangouts video chat have been validated by many. He holds an MBA from St. Mary’s University of MN, a MSST (Master of Science in Security Technologies) degree from the University of Minnesota, and a BA in political science from the University of Wisconsin Eau Claire.

        Three Points on Artificial Intelligence and Cyber-Security for 2017

        icit-new-logo-for-website5
        Although I have been known for longer posts, I would like to offer only three things to watch out for related to artificial intelligence and cyber-security for 2017, followed by sharing two videos.

        1) Cyber attackers have long used machine learning and automation techniques to streamline their operations and may soon use full-blown artificial intelligence to do it. Botnets will become self-healing and will be able to detect when they are being discovered and can re-route in response. The botnet and cyber crime business will grow and become more organized. Showdan, the world’s first search engine for internet connected devices, will be used to target companies and individuals negatively. Yet it can also be used for safety and compliance monitoring, most likely when its feed into another analytical tool.

        How to Hack with Showdan (For Educational Purposes Only):

        2) It won’t be long until A.I. learns the patterns of mutating viruses and then has the ability to predict and/or stop them in their tracks. This is dependent on the most up to date virus definitions, and corresponding algorithms. How a Zero Day is made is heavily a math problem applied to a certain context and operating system. There should be a math formula to predict the next most likely Zero Day exploit – A.I. could provide this. It’s a matter of calculating all possible code various and code add on variations. It’s a lot more advanced than a Rubix Cube.
        975f495fafd8c494591892412ecf87e33) A.I. has the potential to close the gap between the lesser developed world and the developed world. The technology behind A.I. is not limited to big companies like IBM or Microsoft for the long term. We may be surprised with tech start-ups out of the lesser developed world who are very creative. Lack of fiber optic cable connectivity has forced many lesser developed nations to rely heavily on cell tower smartphone based internet communications. This has inspired a mobile app growth wave in parts of Africa as described here; “the use of smartphones and tablets within the country has led to a mobile revolution in Nigeria. Essentially, people now tend to seek mobile solutions more often and thus, enhance the growth of the mobile app development industry” (Top 4 Mobile App development companies in Nigeria, IT News Africa, 2015). A.I. will likely close the gap between these two sectors though not drastically change it. If lesser developed countries can build their own mobile apps and outsource things to A.I.; they could become more independent from the economic constraints of the developed world.

        The below video highlights some of the complications around these points. It is from a conference hosted by the ICIT on April 25, 2016, and I did not attend this. In the video, Donna Dodson (Associate Director, Chief Cybersecurity Advisor and Director, NIST), Mark Kneidinger (Director, Federal Network Resiliency, DHS), Malcolm Harkins (ICIT Fellow – Cylance) and Stan Wisseman (ICIT Fellow – HPE) discuss related concepts and share realistic examples of how these technologies are reshaping the cyber-security landscape.

        ICIT Forum 2016: Artificial Intelligence Enabling Next-Generation Cybersecurity

        If you want to contact me to discuss these concepts click here.

        Five Unique Tech Trends in 2016 and Implications for 2017

        1) Russian Hacking in U.S. Elections – critical infrastructure implications:
        For more than ten years candidates and advocacy groups have used internet marketing hacks to steal their opponent’s websites, redirect internet traffic, or increase negative search results on them by manipulating search engine algorithms. For example, former GOP Presidential candidate Carly Fiorina failed to register carlyfiorina.org and thus had an opposition group use it as negative publicity against her, but she has since acquired the site. Yet 2016 proved to be a turning point in political hacking because of the level and sophistication and sustained effectiveness. The Washington Post reported, “Russian government hackers were able to penetrate DNC servers, compromising opposition files, chats, and emails on republican nominee Donald Trump (Eliza Collins, 12/30/16, USA Today). With this information, Russian intelligence agents masqueraded as third parties to create very believable spear phishing campaigns. These fake emails worked to trick victims into typing in their usernames and passwords after which Russian agents moved further into their networks, undetected at the time.

        On 12/29/16, in a first of its kind move, the Obama Administration released a joint FBI and DHS report (JAR-16-20296: GRIZZLY STEPPE – Russian Malicious – US-Cert) on the technicalities of the hack and sanctioned the GRU and the FSB (Russian intelligence agencies) and key companies they contracted with (Katie Bo Williams, 12/29/16, The Hill). The following diagrams (Fig. 1-a and 1-b) show there were two main hacking groups and that they used mostly classic hacking tactics that were clearly preventable. APT29 hides via encrypted communication and speeds up commands via PowerShell code automation, applied to multiple operating systems. Thus they must have been observing and studying/testing for a while to get this right as its complex across phones, tablets, and PCs. At the same time, APT28 was using a private tunnel (like a VPN) to install and remotely run applications – key loggers designed to steal information and credentials.

        Russian DNC Hack Diagram – Fig. 1 – a: (JAR-16-20296: GRIZZLY STEPPE – Russian Malicious – US-Cert).
        Russian Hack Part 3.png
        All this started as far back as the summer of 2015, so the full penetration went undiscovered for more than a year. In that time, it has been alleged that the hackers were releasing embarrassing info to manufacture fake negative news against Hillary Clinton. In one instance the release of this info resulted in the resignation of the on DNC Chair, Florida Representative Debbie Wasserman Schultz. Yet the hack is not fully partisan because many sources confirmed that, Republican House members, thought leaders and non-profits to the GOP, were also hacked (Jeremy Diamond, 12/16/16, CNN).

        Russian DNC Hack Diagram – Fig. 1 – b: (JAR-16-20296: GRIZZLY STEPPE – Russian Malicious – US-Cert).
        Russian Hack Part 2.png

        On 12/30/16 the Obama Administration took the strong action of expelling thirty-five Russian diplomats in response to the hack. Shortly thereafter they enacted OFAC (Office of Foreign Asset Control) sanctions against Russian business entities associated with these people. They left the country under close U.S. escort on 01/01/17 as they arrived at an airport to depart on a private Russian plane sent by president Putin.

        Alleged Hacker and Russian Spy, Alisa Shevchenko – Fig. 3:
        1483128352073-cachedInterestingly, one of the people expelled, Alisa Shevchenko, was praised a year before by the United States which does not speak well for U.S. intelligence agencies. Specifically, The Department of Homeland Security said “Alisa Shevchenko had helped prevent cyber crime under a program for information sharing between the public and private sector. Ms. Shevchenko was also said to have assisted a French company, Schneider Electric, in identifying vulnerabilities in its software” (Andrew E Kramer, New York Times, 12/31/16). However, we think she may have been a Russian spy all along and could have been inside key U.S. systems at that time but this unconfirmed. Her company, Zora Security, has been a key supplier to the Russian Military’s Main Intelligence Directorate, or G.R.U. In her recent Twitter posts she indicates that she is indifferent to being discovered by the U.S. intelligence agencies. This is likely because she is a close pawn of Putin’s who did a fairly good job going undetected as long as she did. More intel is likely to come out substantiating this.

        At present, the election systems aren’t considered among the sixteen U.S. critical infrastructures and thus they have no federal protection. This is because current law defines the administration of elections as in the hand of each state and these states do not want federal involvement into their election systems out of fear of political persecution. We can understand this (especially Texas) but think some compromise could be accorded if a state election system was targeted by a foreign government, thus making it a national interest. The federal government is less involved in the day to day activities and security of the sixteen critical infrastructures because 80% of them are owned by private enterprises. However, when Sony got hacked in 2014 it became a national issue a few days later and then the Federal government helped out, but afterward, Sony quickly wanted to avoid contact with them. This is because, although well intentioned and large, the federal government is not as good at most I.T. security as the private sector is. Yet the case of multiple state election systems is unique because they are used only for elections and then are put in storage. Ultimately each states voting data rolls up to the federal level and most of this supply chain is at risk to hacking and manipulation. Thus, the maintenance and updates of these systems and the systems used by dispersed political parties for campaigns need to be improved. This may require some sort of hybrid-critical infrastructure protection, increased private sector partnership, or just more dollars spent by the state election bodies and political parties. Why are commercial facilities and their systems more important than the systems that track election activity and results in a country that fought several wars to stay democratic? By including the election process and systems as a critical infrastructure or hybrid-critical infrastructure, researchers and entrepreneurs will be inspired to improve the process, all the while sustaining or increasing privacy which is a must for a nation as diverse as the United States. More news outlets, advocacy groups, consultants, and academics need to debate this publicly!

        2) Tesla and the Growth of the Electric car – decline of the gasoline based car: 
        2016 was a profound year of announcements when it comes to the market for electric cars. Many car manufacturers have been playing catch up with Tesla for a few years now. That being said, several companies have produced versions of their own electric car. But there are very few that have produced an electric car designed from the ground up. The Nissan Leaf and BMW i3 were two of those, and as of November 2016 Chevrolet started manufacturing its Bolt EV. Mercedes also announced that it will have several different types of electric vehicles soon. This includes their urban electric-powered straight truck (Fig. 3) which has self-driving capabilities. This would allow inter-city delivery on an EV platform.

        Mercedes Electric Self-Driving Truck Prototype – Fig. 3:

        mercades-self-driving-truckSimply put, the market is starting to catch up to Tesla. 2017, we think will be the year that makes or breaks Tesla. If Tesla can ramp up production like it plans to, it will continue to maintain market share. By 2018, it has audacious production goals of a half million. With just about every major automotive company producing plans for electric vehicles, competition for this segment will start to get really competitive.

        3) Self-Driving Cars – personal and commercial:
        Google has been developing a self-driving car for a few years now, but it has been slow to fully develop and bring them to market. In fact, a few of Google’s employees left to start their own company for self-driving trucks. That company, Otto, was recently sold to Uber for $680 million (Mark Harris, Business Insider – Back Channel, 12/03/16). Uber has also been working on self-driving cars with its Ford Fusion line. Now, these cars still have people behind the wheel just in case of an emergency, but it’s the next step in fully rolling out an autonomous fleet of vehicles. Uber gave their fleet of Volvo XC-90s a try for only a week in San Francisco but picked up and moved on to Arizona to continue testing. This was because they didn’t want to comply with California DMV requirements to file paperwork and pay a registration fee. Otto, on the other hand, also made their first delivery of Budweiser beer in Colorado (Fig. 4).  

        Otto Self-Driving Budweiser Delivery Video – Fig. 4:

        This is dawning the start of Uber Freight where shippers can ship through an Uber App for their truckloads. C.H. Robinson and Amazon are both developing apps like this. We think before cars get the green light to drive in inner-cities, self-driving semis will get the regulatory green light, firstly on interstates. This is because commercial vehicles cost a lot more, are bigger, serve thousands of customers per year, thus the investment in self-driving technology is a justified priority in spite of any risk.  Additionally, commercial shipping is automated in most parts of the supply chain and this is a precursor for self-driving trucks. The NHTSA did publish guidelines on self-driving cars and their testing in September (link here). We think 2017 will be the year of testing self-driving vehicles and in 2018 it will start to become a mass market idea.

        4) Surveillance via Smart Phones – privacy implications:
        Smartphones are small supercomputers that house more personal info on their users and families than any other device in modern history. From texts, PHI, fingerprint scans, downloaded documents, contact lists, photos, geolocation tags, the use of many cloud databases – both upload and download, and apps that take away some of our privacy – via partial and full consent. A smart phone is more advanced than any gadget dreamed up by 007 and the need for privacy on it is just as important.

        2016 proved to be a turning point in the privacy vs. government surveillance debate. It intensified after the mass shooting in San Bernardino, CA, which happened at the end of 2015, killing 14 people. Then in 2016 the government sued Apple to get them to build a backdoor into the perpetrators iPhone to which Apple strongly objected. The government eventually broke into them phone shortly thereafter with the help of Israeli tech contracts. Keep in mind that ever since Edward Snowden leaked NSA documents in 2013 about the government’s overreach into technology companies, to get them to build back doors, it has become more politically acceptable to resist such demands. Congress has made very minor surveillance rollbacks, mostly related to phone metadata but much more work needs to be done (Ellen Nakashima, The Washington Post, 11/27/15).

        Andriod phones have also suffered hacks and backdoors.  A source described it this way, “security experts say they have discovered secret ‘backdoor’ software in some Android phones that sends users’ personal data to China. Kryptowire, the security firm that discovered the vulnerability, confirmed this information on its website on Tuesday. The firm wrote that certain Android devices contain pre-installed software that collects and sends personal data, such as texts and geographical location, to an unauthorized third-party” (New York Times, 11/15/16).  This is a clear blow to android privacy and will require costly R&D by Google.  With the growth of third party phone applications these risks will continue to increase and get more complicated.

        Illustration of Apple vs. The FBI – Fig. 5:
        1458594148060
        Although the government argues that back doors make the nation safer, this makes no logical sense and there are no real world case studies to support it. First of all, the fact that the government needs to rely on the private sector for such backdoors and tech consulting proves that the private sector is where technology innovation comes from and that supports the concept of intense free competition.

        The U.S. intelligence agencies would not be much better than a “drunken inspector gadget” without third-party consultants and tech firms. Key private sector innovation in the military industrial complex has helped this nation win wars and secure freedom for all – way back to the founding of the Union. This includes stealth fighter technologies, radar technologies, canons, and it does not require government overreach or back doors. The government is a paying customer of the best tech products and has always been.  

        Yet when the same consultants and tech firms serve regular customers, like Apple with the iPhone, those customers have a reasonable expectation of privacy and quality. This should not diminish merely because the government can’t solve a crime or problem quickly. Apple CEO Tim Cook described the government’s request this way, “it’s the software equivalent of cancer. He said he was prepared to take the fight all the way to the Supreme Court. This would be bad for America, he said. It would also set a precedent that I believe many people in America would be offended by” (Enjoli Francis, ABC News, 02/24/16). There are far more security benefits in keeping private technology data private. This includes privacy after domestic breakups, privacy from cyber-stalking, privacy from annoying marketing, privacy from political persecution and harassment. Also, Government agencies can use these same private technologies to conduct military and intelligence operations without worrying about being hacked by opposing governments or terrorists.

        In 2017 we think technology companies will increase the security of their products, and companies like Apple and Google are already in the process of doing this. In Apple’s case, they have spent millions to hire encryption legend Jon Callas, who invented PGP encryption, to redesign the security of their products (Reuters, 05/24/16). We think most company shareholders, investors, customers, and finance people now see the additional cost to build in great security as required.  To customers, security on a product is worth a price premium and a globally competitive company must have secure products.

        We also think policy makers will have to do more to accommodate the privacy concerns of citizens, perhaps partly like the E.U. has done. We also think 2017 will further debunk the connection between backdoor system hacks and terrorism prevention. Clearly, monitoring the entire free world’s metadata is a violation of democratic norms, and it waters down security greatly because it can easily be manipulated for every imaginable bad reason. Most likely, setting people up, and government leaders throughout all history like to find people to blame for their problems/misdeeds. Yet behavioral profiling and good traditional police and intelligence work in conjunction with advanced sustained diplomatic dialogue with a range of diverse groups, friends and enemies alike, should produce better intelligence for more specific actionable results. The intelligence community has thousands of tech tools to use to secure the nation, mostly private sector based, so they don’t need to monitor all metadata.

        5) Using Drones for Last Mile Deliveries – suited for rural and high traffic areas:

        Amazon Prime Drone via Prime air – Fig. 6:
        imagesAmazon made its first test delivery by a drone in the U.K. in 2016. This will continue to be developed as Amazon continues to test and tweak its system for making deliveries by drone. In fact, this is one of many programs where Amazon is developing its systems in “last mile” delivery. They also currently have their own fleet of vans to deliver and they use their Flex program of drivers to pick up and deliver packages. They also recently filed a patent for “floating warehouses” where these would have inventory in an airship that drones could pick up products and then deliver them, for example to a sporting event (Kate Abbey-Lambertz, 12/30/16, Huffington Post). Realistic but far out innovation like this will continue to challenge UPS and FedEx to provide a better customer experience. Drone delivery is just one idea. The benefit or idea behind drone delivery is that it could deliver to customers within a half hour. This would drastically improve the time to deliver to its customers. Currently, with Prime Now, you can get one-hour and two-hour delivery in certain areas.  

        We think Amazon will continue to develop its drone delivery in 2017 by testing it in many countries across the world. The FAA in the U.S. has been one roadblock to Amazon testing in the United States. This is just one agency that is figuring out how to regulate this new technology as it tries to prevent small planes and traffic from colliding with drones. Amazon’s competitors are watching and we’ll see how far they get in 2017.

        jeremy-swensonmike-cassem
        Jeremy Swenson and Mike Cassem are two seasoned, part-time, Intel certified, retail technology marketing and training representatives on assignment at Best Buy for clients including Intel, H.P., Trend Micro, Adobe, and others – presently on sabbatical. They also spent five years crafting their public speaking and writing skills in Toastmasters International. For full-time work, Swenson doubles as a Sr. business analyst, process improvement and project management consultant. While Cassem doubles as a marketer and sales logistics analysis consultant. Tweet to them @jer_Swenson and @micassem.

        Microsoft HoloLens, Mobile vs. Good Web-Design, and Security Needs Innovation Not Gov’t.

        Microsoft HoloLens1) We knew there would come another well-positioned company who makes a pair of smart glasses like Google Glass and that it will derive more competition and innovation. Microsoft raised their hand right away with their HoloLens glasses which are hologram based, slightly “gamified”, and seemingly better than Google Glass largely because they tied it in with known Windows functionality (broader offerings). See a video of this cool new technology here:

        2) It is a fact that on average people now access more of their e-mail via mobile devices more often than on a traditional computer. This has forced websites, news makers, and companies to design their web offerings in a mobile compatible design so when you go to the web on a computer the sites are often overly mobile in their design aspects and sometimes look goofy and the buttons and frames are too big. CNN.com is a good example of a web-site that went too far with their mobile design so if you access it from a normal computer it looks more like a kids play web-site with big buttons and frames optimized for touch with little info presented. Yet their prior design was better especially if you want to read more on one screen view.

        (Old vs. New CNN.com, respectively)
        Old and New CNN WebsiteThere is no doubt that mobile will continue to grow and will be used on smaller devices like watches, ear buds, pacemakers, and contact lenses. Web design has shifted so fast to mobile that sometimes good web design and user experience is forgotten about for non-mobile users or business users who on average spend much more time on those same sites than mobile users. Thus a better balance of the two design types is needed, and an app is a separate project all together yet still needed. I also think Microsoft will take more mobile market share away from Android and Apple since they have learned a lot from their Windows 8 release and are quickly working to release Windows 10 as a better touch based mobility optimized O.S. that many are excited to try.

        3) There will be more data breaches but many of them will be supported by the Western Governments who in effect devalue security standards by corroborating with large companies to quarry vast amounts of metadata all in the name of security. Sadly we know Governments have abused this power in the past and will continue to do so thus the private sector needs to collaborate and inspire innovation in this space for better security and transparency so the masses may have security and corrupt Governments can be exposed.

        Equation group victims map

        As it stands now hackers are a few steps ahead of antivirus makers and they are constantly tweaking their viruses so they can’t be detected. The newest types of viruses are suspected to be created by the Equation Group, one of the most sophisticated hacking groups ever known. These new viruses hide in your hard drives firmware and are undetectable. Antivirus maker Kaspersky commented on this in their Q&A doc on the Equation Group by stating, “We were able to recover two HDD firmware reprogramming modules from the EQUATIONDRUG and GRAYFISH platforms. The EQUATIONDRUG HDD firmware reprogramming module has version 3.0.1 while the GRAYFISH reprogramming module has version 4.2.0. These were compiled in 2010 and 2013, respectively, if we are to trust the PE timestamps” (http://25zbkz3k00wn2tp5092n6di7b5k.wpengine.netdna-cdn.com/files/2015/02/Equation_group_questions_and_answers.pdf).

        Kaspersky went on to further speculate that there were clues that the U.S. N.S.A. was involved in the latest hard drive firmware virus and even suggested they had the cooperation of major hard drive makers like Western Digital, Seagate, Samsung, and Toshiba in order to get the code needed to write the virus. Any reasonable technologist would likely agree with this. Yet this decreases innovation and free competition and you know big money likely traded hands to make these deals happen. How can a big company now trust paying a technology company for security or services when they are just going to give it away to supposed governments here or elsewhere? More importantly, if one government has the ability to get into a tech companies data, then other more ill-intentioned governments and organizations can quickly learn how to do that as well and that is the real threat.

        If you want to hire me to speak at your next event or consult for your company on these and related topics please contact me.