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Security with AI and Machine Learning
Today, threats are not only more prevalent, but they're more sophisticated as well. Fortunately, tools that use AI and machine learning are better equipped to stand up to challenges than their predecessors. In this ebook, Oracle Dyn's Laurent Gil and Recorded Future's Allan Liska look at the pros and cons of AI- and ML-based security tools to combat threats.
By the end of this ebook, you'll understand:
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
By the end of this ebook, you'll understand:
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
64 pages, ebook
First published October 8, 2018
1 person is currently reading
6 people want to read
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