Third-Wave AI

Whitepaper: The False Promises of AI in Cybersecurity

Cybersecurity is a battlefield where innovation is paramount. Artificial intelligence (AI) has emerged as a potential game-changer, promising to revolutionize threat detection and response. Vendors have made bold claims, promising their AI-powered solutions will provide unparalleled capabilities, eliminate false positives, and autonomously defend against even the most sophisticated attacks.

Unveiling the Power: A Strategic Look at the Benefits of Using AI in Cybersecurity

If you’ve followed this blog series, you already know that Artificial intelligence (AI) has become a ubiquitous term, holding immense promise across various industries. Cybersecurity is no exception, with AI poised to revolutionize how organizations defend their data and systems against malicious activity. However, a crucial question remains: Are cybersecurity teams effectively harnessing AI’s potential for maximum security impact?

Navigating the Maze: A Measured Approach to AI Adoption in Cybersecurity

While a significant portion (53%) of respondents acknowledge their organization’s early-stage adoption of AI, only 18% report full deployment into integrated security programs. This cautious approach reflects the need for careful planning and implementation to ensure AI enhances, rather than hinders, security posture.

The AI Advantage: Mitigating the Security Alert Deluge in a Talent-Scarce Landscape

The cybersecurity landscape is under siege. Organizations are bombarded by a relentless barrage of security alerts, often exceeding a staggering 22,111 per week on average. While Artificial Intelligence (AI) has emerged as a powerful tool to manage this overwhelming volume, its effectiveness isn’t without limitations, as vendors flood the market with false advertising and promises.

Unveiling The Applications and Distinctions of Machine Learning and Artificial Intelligence in Cybersecurity

The terms “machine learning” and “artificial intelligence” are frequently used in cybersecurity, often interchangeably, leading to confusion about their precise meanings and applications. Both machine learning and artificial intelligence play pivotal roles in fortifying cybersecurity defenses, yet they encompass distinct methodologies and applications. What are the disparities between them? And how do these technologies converge to bolster cyber resilience?

AI and Cybersecurity: A Rob Burgundy Investigation

Attention, fellow news anchors and concerned citizens! Rob Burgundy is here to tackle a story hotter than a disco inferno in polyester pants: Artificial Intelligence (AI) and Cybersecurity. That’s right, folks. In this digital age, hackers are running rampant like greased weasels in a chicken coop, stealing our precious data faster than you can say “glass case of emotion.” But fear not, for organizations are turning to a new weapon in this cyber war: AI, the thinking machine!

Understanding the Joe Biden Executive Order on AI and Enhancing Cybersecurity: Key Takeaways and Recommendations

On October 30, 2023, the White House issued an Executive Order promoting safe, secure, and trustworthy artificial intelligence (AI) deployment. This Executive Order recognizes the global challenges and opportunities presented by AI and emphasizes the need for collaboration, standards development, and responsible government use for national security.

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

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.