Malware data science: attack detection and attribution, joshua saxe, hillary sanders
Описание
Malware Data Science
explains how to identify, analyze, and classify large-scale malware using
machine learning and data visualization.
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 visualization, and shows you how to apply
these methods to malware detection and analysis.
You'll learn how to:
- 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.
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