Table of Contents for
Machine Learning and Security

Version ebook / Retour

Cover image for bash Cookbook, 2nd Edition Machine Learning and Security by David Freeman Published by O'Reilly Media, Inc., 2018
  1. nav
  2. Cover
  3. Praise for Machine Learning and Security
  4. Machine Learning and Security
  5. Machine Learning and Security
  6. Preface
  7. 1. Why Machine Learning and Security?
  8. 2. Classifying and Clustering
  9. 3. Anomaly Detection
  10. 4. Malware Analysis
  11. 5. Network Traffic Analysis
  12. 6. Protecting the Consumer Web
  13. 7. Production Systems
  14. 8. Adversarial Machine Learning
  15. A. Supplemental Material for Chapter 2
  16. B. Integrating Open Source Intelligence
  17. Index
  18. About the Authors
  19. Colophon

Praise for Machine Learning and Security

The future of security and safety online is going to be defined by the ability of defenders to deploy machine learning to find and stop malicious activity at Internet scale and speed. Chio and Freeman have written the definitive book on this topic, capturing the latest in academic thinking as well as hard-learned lessons deploying ML to keep people safe in the field.

Alex Stamos, Chief Security Officer, Facebook

An excellent practical guide for anyone looking to learn how machine learning techniques are used to secure computer systems, from detecting anomalies to protecting end users.

Dan Boneh, Professor of Computer Science, Stanford University

If you’ve ever wondered what machine learning in security looks like, this book gives you an HD silhouette.

Nwokedi C. Idika, PhD, Software Engineer, Google, Security & Privacy Organization