Security with AI and Machine Learning

Security with AI and Machine Learning

For security professionals seeking reliable ways to combat persistent threats to their networks, there's encouraging news. Tools that employ AI and machine learning have begun to replace the older rules- and signature-based tools that can no longer combat today's sophisticated attacks. In this ebook, Oracle's Laurent Gil and Recorded Future's Allan Liska look at the strengths (and limitations) of AI- and ML-based security tools for dealing with today's threat landscape.

This high-level overview demonstrates how these new tools use AI and ML to quickly identify threats, connect attack patterns, and allow operators and analysts to focus on their core mission. You'll also learn how managed security service providers (MSSPs) use AI and ML to identify patterns from across their customer base.

This ebook explains:

  • Why rules-based, signature-based, and firewall solutions have fallen short;
  • How automated bots enable cybercriminals and nation-state actors to attack your network;
  • The evolution of the botnet: how threat actors constantly change their attack strategy;
  • How AI and ML techniques in web applications help you observe, quantify, and classify inbound requests;
  • How to detect insider threats and advanced persistent threat actors with AI and ML tools;
  • Case studies that show how a media company, an airline, and a university use AL and ML in security.



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