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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.
Categories:Computers - Security
Year:2018
Edition:Paperback
Language:english
Pages:272
