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

AI, artificial intelligence, Blog, Machine Learning, Self-Supervised AI, Third-Wave AI, Uncategorized / By

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

AI, Blog, generative AI, Ponemon, Predictive AI, Self-Supervised AI, SOC, Third-Wave AI, Unsupervised AI / By

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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A Proven Strategy For Defending Against Zero-Day Exploits And Attacks — Updated for 2023

Blog, Unsupervised AI, Zero Day Attacks / By

Zero-day attacks are considered the number one cybersecurity threat to company networks large and small. Understand what they are, why it’s so hard to detect them, and how artificial intelligence (AI) is helping to solve this modern problem.

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Don’t Fall for the Hype – Marketing Myths in Artificial Intelligence for Cybersecurity

Blog, Product Updates, Unsupervised AI / By

The cybersecurity provider landscape is cluttered with impossible claims, misrepresentations, and a confusing mix of inconsistent terminology. Worse, every minute you delay making a decision is another minute hackers have to gain access and knowledge about your network.

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The Difference Between Artificial Intelligence and Machine Learning in Network Security

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Artificial Intelligence (AI) and Machine Learning (ML) are often used interchangeably when discussing developments in deep learning. However, there is an important difference between the two that network security professionals will need to understand in order to serve their clientele effectively.

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AI-Enabled Cybersecurity Is Necessary for Defense: Capgemini Report

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850 senior executives from Information Security, Cybersecurity, and IT Operations in seven industries across ten countries were recently surveyed by consulting and technology services firm, Capgemini, in their “Reinventing Cybersecurity with Artificial Intelligence” report. The goal being to understand today’s benefits, complexities, and levels of implementation of AI in cybersecurity across IT (information technology), OT (operation

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The Endpoint Gap in Corporate Security

Blog, Network Detection and Response, Unsupervised AI / By

“The biggest misconception people have about endpoints is that they have an idea of what their endpoints really are. The security industry has rightly taught defense-in-depth & blocking. However, too many companies rely solely on that concept, and aren’t prepared for what happens when something is breached. That breach, when it happens, will take place

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