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Whitepaper: The False Promises of AI in Cybersecurity

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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.

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AI: Friend or Foe? Unveiling the Current Landscape with MixMode’s State of AI in Cybersecurity Report

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If you’ve been following along in this series, you already know that Artificial Intelligence (AI) has emerged as a powerful tool for organizations to strengthen their cybersecurity defenses. But how is AI being used in cybersecurity today, and what are its key benefits?

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Unlocking the Power of True AI: MixMode’s Cutting-Edge Cybersecurity Solution

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We have now reached the Third wave of AI: Contextual Reasoning. This revolutionary approach, pioneered by MixMode in cybersecurity, utilizes self-supervised and explainable AI to independently learn and adapt without reliance on rules or training data.

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

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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.

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

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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.

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The Evolving Threat Landscape: Why AI is Essential for Cybersecurity Success

Adversarial AI, AI, Blog, Cybersecurity Industry, Cybersecurity News, generative AI, infrastructure, Third-Wave AI / By

This week, we’re looking into how the rise of artificial intelligence (AI) has significantly altered the threat landscape, introducing challenges and opportunities for organizations seeking to safeguard their data and infrastructure.

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

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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?

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AI and Cybersecurity: A Rob Burgundy Investigation

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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!

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Chat GPT and Nation-State Attackers: A New Era of AI-generated Attacks

Adversarial AI, AI, Blog, Context-Aware AI, Cyber Attacks, Malware, Phishing, Third-Wave AI / By

A new report from Microsoft and Open AI shows how attackers are increasingly using artificial intelligence (AI) to improve their cyberattacks. The report found that nation-backed groups use LLMs for research, scripting, and phishing emails.

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Navigating the Uncertain Path: Why AI Adoption in Cybersecurity Remains Hesitant, and How to Move Forward

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Despite AI’s potential to help defend against cyber attacks, AI adoption in cybersecurity practices remains in its early stages. Why is this the case, and how can organizations overcome these hurdles to pave the way for a secure future?

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Harnessing the Power of Advanced AI to Optimize Security

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Organizations continue to face increasingly sophisticated cyber threats that require a proactive and adaptive approach to cybersecurity. As the volume and complexity of security data grows, security professionals are turning to advanced AI technologies to enhance their capabilities and stay ahead of emerging threats.

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

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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.

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Advanced Behavioral Detection Analytics: Enhancing Threat Detection with AI

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Gartner just released its Emerging Tech Impact Radar: Security, which looked at technologies that could help organizations effectively detect and respond to attacks and create better efficiencies through AI-based security hyper-automation.

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

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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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Gartner Security & Risk Management Summit 2023 Recap

AI, Cloud Security, Cybersecurity News, Gartner, generative AI, SIEM, Third-Wave AI, Uncategorized / By

One of the key predictions is that by 2027, 50% of chief information security officers (CISOs) will adopt human-centric design practices in their cybersecurity programs to minimize operational friction and maximize control adoption. This approach focuses on designing security controls around individuals rather than technology or threats. It recognizes that employees play a crucial role in cybersecurity and aims to reduce the likelihood of risky behavior.

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Forbes Technology Council: Why Large Language Models (LLMs) Alone Won’t Save Cybersecurity

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The star of the moment is Large Language Models (aka LLMs), the foundational model that powers ChatGPT. There are plenty of documented examples of truly impressive feats built on this technology: writing reports or outputting code in seconds. At its core, LLMs basically ingest A LOT of text (e.g., think Internet) as a corpus of training data and rely on human feedback in a type of supervised training called reinforcement learning.

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