Security has become a 'big data' problem. The growth rate of malware has accelerated to tens of millions of new files per year while our networks generate an ever-larger flood of security-relevant data each day. In order to defend against these advanced attacks, you'll need to know how to think like a data scientist. In Malware Data Science, security data scientist Joshua Saxe introduces machine learning, statistics, social network analysis, and data visualisation, and shows you how to apply these methods to malware detection and analysis.

Malware Data Science explains how to identify, analyze, and classify large-scale malware using machine learning and data visualization.

About the Author
Joshua Saxe is Chief Data Scientist at major security vendor, Sophos, where he leads a security data science research team. He's also a principal inventor of Sophos' neural network-based malware detector, which defends tens of millions of Sophos customers from malware infections. Before joining Sophos, Joshua spent 5 years leading DARPA funded security data research projects for the US government.

Hillary Sanders leads the infrastructure data science team at Sophos, which develops the frameworks used to build Sophos' deep learning models. Before joining Sophos, Hillary created a recipe web app and spent three years as a data scientist at Premise Data Corporation.

Reviews
"For those looking to become a security data scientist, or just want to get a comprehensive understanding of how to use data science to deal with malicious software, Malware Data Science is a superb reference."
-Ben Rothke, RSA Conference


"If you are new to data science or machine learning, this book provides an excellent introduction to these topics."
-DMFR Security



Book Information
ISBN 9781593278595
Author Joshua Saxe
Format Paperback
Page Count 272
Imprint No Starch Press,US
Publisher No Starch Press,US
Weight(grams) 622g