Machine Learning and Security: Protecting Systems with Data and Algorithms 1st Edition

We wrote this book to provide a framework for discussing the inevitable marriage of two ubiquitous concepts: machine learning and security. While there is some literature on the intersection of these subjects (and multiple conference workshops: CCS's AISec, AAAI's AICS, and NIPS's Machine Deception), most of the existing work is academic or theoretical. In particular, we did not find a guide that provides concrete, worked with examples code that can educate security practitioners data about science and help machine learning practitioners think about modern security problems effectively.

In examining a broad range of topics in the security space, we provide examples of machine learning how can be applied to augment or replace rule-based or heuristic solutions to problems like intrusion detection, malware classification, or network analysis.