Machine Learning and Security by Clarence Chio, Paperback, 9781491979907 | Buy online at The Nile
Paperback
In this practical guide, machine learning and security specialists Clarence Chio and David Freeman provide a framework for discussing the marriage of these two fields, as well as a toolkit of machine-learning algorithms that you can apply to an array of security problems.

Machine Learning and Security

Protecting Systems with Data and Algorithms

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$137.97

  • Paperback

    370 pages

  • Release Date

    23 February 2018

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Summary

Can machine learning techniques solve our computer security problems and finally put an end to the cat-and-mouse game between attackers and defenders? Or is this hope merely hype? Now you can dive into the science and answer this question for yourself. With this practical guide, you’ll explore ways to apply machine learning to security issues such as intrusion detection, malware classification, and network analysis.

Machine learning and security specialists Clarence Chio and David Fr…

Book Details

ISBN-13:9781491979907
ISBN-10:1491979909
Author:Clarence Chio, David Freeman
Publisher:O'Reilly Media
Imprint:O'Reilly Media
Format:Paperback
Number of Pages:370
Release Date:23 February 2018
Weight:666g
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About The Author

Clarence Chio

Clarence Chio has a B.S. and M.S. in Computer Science from Stanford, specializing in data mining and artificial intelligence. He has spoken on machine learning and/or security at DEF CON and 11 other infosec/software engineering conferences in 8 countries between 2015 and 2016. He had been a community speaker with Intel, and a security consultant for Oracle. Clarence currently works as a Security Research Engineer at Shape Security, building a product that protects high valued web assets from automated attacks. He is also the founder and organizer of the “Data Mining for Cyber Security” meetup group, the largest gathering of security data scientists in the San Francisco Bay Area.David Freeman is head of Anti-Abuse Relevance at LinkedIn, where he leads a team of machine learning engineers charged with detecting and preventing fraud and abuse across the LinkedIn site and ecosystem. He has a Ph.D. in mathematics from UC Berkeley and did postdoctoral research in cryptography and security at CWI and Stanford University.

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