Saxe, Joshua
Malware Data Science: Attack, Detection, and Attribution
- ISBN 13:
- 9781593278595
- author:
- Saxe, Joshua
- format:
- Paperback
- publisher:
- No Starch Press,US
- language:
- English
- Publication Year:
- 2018
- Pages:
- 400
- Dimensions:
- 22.35 x 17.78 x 1.78 centimetres
- Genre:
- Computers, Special Topics, Viruses,
- Condition:
- New
- Availability:
- Item usually sent within 10 working days
Description
Malware Data Science: A Guide to Identifying and Analyzing Malicious Software Using Machine Learning and Data Visualization. The threat of malware has become increasingly complex, with tens of millions of new files emerging every year. To defend against these advanced attacks, you need to think like a data scientist. This book introduces machine learning, statistics, social network analysis, and data visualization, and shows how to apply these methods to malware detection and analysis. You'll learn how to analyze malware using static analysis, observe its behavior through dynamic analysis, identify adversary groups through shared code analysis, and catch 0-day vulnerabilities by building your own machine learning detector. The book also covers measuring malware detector accuracy and identifying 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.
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