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Machine learning and security : protecting systems with data and algorithms

By: Chio, Clarence
Title By: Freeman, David
Material type: BookPublisher: Beijing, China : O'Reilly, c2018.Description: xv, 365 p. : ill. ; 24 cm.ISBN: 9781491979907Subject(s): Computer security | Machine learning | AlgoritmenDDC classification: 006.31 CH MA Online resources: Ebook Link
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 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. This book is ideal for security engineers and data scientists alike --
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Item type Home library Call number Status Date due Barcode Item holds
eBook University of Wollongong in Dubai
eBook
006.31 CH MA (Browse shelf) Available T0065586
Total holds: 0

Includes bibliographical references and index.

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 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. This book is ideal for security engineers and data scientists alike --

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