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Geoffrey Coulehan

Geoffrey is a cybersecurity business executive and leader with over 25 years of experience and a proven track record in sales and solutions across a wide variety of information security technologies, risk management, and regulatory compliance solutions. Geoffrey currently runs Strategic Alliances at MixMode and before coming to MixMode he ran large solutions teams at Splunk, Palo Alto Networks, and SAP.

CISOs: Are You Applying NIST / CISA Standards to ALL Data Including the Cloud?

AI, Blog, CISO, Cloud Security, Cloudtrail, generative AI, Third-Wave AI / By

Security leaders want to solve problems identifying and understanding anomalies or account access behaviors by correlating anomalous behaviors of specific accounts with other parameters like geography or ingress and egress points, but few rules-based Cybersecurity tools have the ability to do that without a great deal of manual data massaging and manipulating.

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Evolving Role of the CISO: From IT Security to Business Resilience

artificial intelligence, Blog, CIO, CISO, Municipalities, Third-Wave AI / By

With more and more large organizations relying on technology to conduct business, the need for a skilled CISO has become increasingly important. No longer just overseeing IT security efforts, the CISO is now responsible for a wide range of cyber defenses from data protection to compliance and even physical security.

Evolving Role of the CISO: From IT Security to Business Resilience Read More →

Third-wave AI has Proven More Effective than Traditional Cybersecurity Platforms and Methodologies

Blog, Network Security, Self-Supervised AI, SIEM, SOC, Third-Wave AI / By

Unfortunately, the majority of cybersecurity solutions available today rely on outdated applications for AI. So-called first- and second-wave AI solutions don’t cut it, but few vendors have the technical capabilities and know-how to apply cutting edge, third-wave AI to their platforms.

Third-wave AI has Proven More Effective than Traditional Cybersecurity Platforms and Methodologies Read More →

Cybersecurity Spend for Data Retention and Analysis is Out of Control and Largely Unnecessary

Blog, Data Storage Cost, Log Data, SIEM / By

Managing a relatively small, stable data store is one thing, but dynamic companies face immense challenges when those circumstances change. Data growth can become unwieldy to safeguard when it has to be carefully prepared through a series of time-consuming, manual processes before the security software can evaluate it.

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Incremental Stacking of Correlative Analysis Platforms Will Ultimately Prove Ineffective and Costly

Blog, CISO, Network Baselines, Network Security, Predictive AI, Self-Supervised AI, SIEM, SOC, Unsupervised AI / By

On the surface, an “incremental stacking” approach to correlative analysis platforms like SIEM, XDR and UEBA is logical. Organizations can overcome some of the inherent limitations present in their security solutions by adding a network traffic analysis (NTA), for example. Industry analysts have been touting this approach for some time now as necessary for full coverage enterprise security.

Incremental Stacking of Correlative Analysis Platforms Will Ultimately Prove Ineffective and Costly Read More →

A Modern SOC Should Not Be Entirely Dependent On Human Operators and Their Personal Experience

Blog, False Positives, SIEM, SOC, Third-Wave AI, Zero Day Attacks / By

A modern SOC should not be entirely dependent on human operators and their personal experience. The issue has been a foundational problem with not only the methodologies used by SOCs for the past 15 to 20 years, but it should be questioned whether the problem is actually compounded by the technology itself.

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How Self-Supervised AI Tackles Ambiguity in Network Security

Blog, Context-Aware AI, Log Data, Network Baselines, Network Detection and Response, Network Security, Predictive AI, Self-Supervised AI, SIEM, Third-Wave AI / By

Cybersecurity vendors promise the moon when it comes to AI. As the recent TechRepublic article, “Why cybersecurity tools fail when it comes to ambiguity,” makes clear, often, these promises fail short in real world network environments.

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Whitepaper: The Failed Promises of SIEM

Blog, Data Overload, False Positives, Regulations & Compliance, Self-Supervised AI, SIEM, SOC, Whitepaper / By

The fundamental SIEM flaws lie in the platform’s need for continual adjustment, endless data stores, and a tendency to create an overwhelming number of false positives. When organizations instead turn to a next-generation cybersecurity solution, which predicts behavior with an unsupervised (zero tuning) system, they are poised to save on both financial and human resources.

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