Machine Learning and Security: Protecting Systems with Data and Algorithms

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. 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.

Book contents:

  1. Why Machine Learning and Security?

  2. Classifying and Clustering

  3. Anomaly Detection

  4. Malware Analysis

  5. Network Traffic Analysis

  6. Protecting the Consumer Web

  7. Production Systems

  8. Adversarial Machine Learning

  9. Supplemental Material for Chapter 2

  10. Integrating Open Source Intelligence