Description
- Analyze malware using static analysis
- Observe malware behavior using dynamic analysis
- Identify adversary groups through shared code analysis
- Catch 0-day vulnerabilities by building your own machine learning detector
- Measure malware detector accuracy
- Identify malware campaigns, trends, and relationships through data visualization Whether you're a malware analyst looking to add skills to your existing arsenal, or a data scientist interested in attack detection and threat intelligence, Malware Data Science will help you stay ahead of the curve.
Author: Joshua Saxe, Hillary Sanders
Publisher: No Starch Press
Published: 09/25/2018
Pages: 272
Binding Type: Paperback
Weight: 1.30lbs
Size: 8.80h x 7.00w x 0.70d
ISBN13: 9781593278595
ISBN10: 1593278594
BISAC Categories:
- Computers | Security | Viruses & Malware
- Computers | Security | Network Security
- Computers | Data Science | Machine Learning
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.