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Security with AI and Machine Learning
book

Security with AI and Machine Learning

by Laurent Gil, Allan Liska
February 2019
Intermediate to advanced content levelIntermediate to advanced
70 pages
1h 28m
English
O'Reilly Media, Inc.
Content preview from Security with AI and Machine Learning

Chapter 2. Understanding AI, ML, and Automation

Prior to discussing the ways in which you can use ML and AI to help your defenders better protect your organization, let’s step back and define the terms. There is a lot of confusion around the definition of ML and AI and how the technologies interact with each other. In addition to defining these terms, no discussion of ML and AI is complete if it doesn’t touch on automation. One of the overarching goals of both ML and AI is to reliably automate the process of identifying patterns and connections. In addition, and specifically to security, ML and AI allow security teams to reliably automate mundane tasks, freeing analysts to focus on their core mission, as opposed to spending their days chasing false positives.

AI and ML

Although many people in the industry have a tendency to use the terms AI and ML interchangeably, they are not the same thing. AI is defined as the theory and development of computer systems that are able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages. With AI, machines demonstrate “intelligence” (some call this the “simulation of an intelligent behavior”), in contrast to the natural intelligence displayed by humans. The term is applied when a machine mimics cognitive functions that humans associate with other human minds, such as learning and problem solving.

Machine learning is an application of AI that ...

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Publisher Resources

ISBN: 9781492043133