This book provides a framework for discussing the interaction of two concepts: machine learning and security. Authors Clarence Chio and David Freeman examine a broad range of topics in the security space, and provide examples of how machine learning can be applied to augment or replace rule-based or heuristic solutions to problems like intrusion detection, malware classification, or network analysis. In addition to exploring the core machine learning algorithms and techniques, the authors focus on the challenges of building maintainable, reliable, and scalable data mining systems in the security space.

Worked examples and guided discussions are used to show how to think about data in an adversarial environment and how to identify the important signals that can get drowned out by noise.

Author: Clarence Chio and David Freeman
Publisher: O'Reilly
Date: Feb 2018
Pages: 386
ISBN: 978-1491979907
Print: 1491979909
Kindle: B079C7LKKY
Audience: developers interested in security
Level: Intermediate
Category: Artificial Intelligence and Security 

• Learn how machine learning has contributed to the success of modern spam filters
• Quickly detect anomalies, including breaches, fraud, and impending system failure
• Conduct malware analysis by extracting useful information from computer binaries
• Uncover attackers within the network by finding patterns inside datasets
• Examine how attackers exploit consumer-facing websites and app functionality
• Translate your machine learning algorithms from the lab to production
• Understand the threat attackers pose to machine learning solutions

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