Malware data science

attack detection and attribution

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Joshua Saxe: Malware data science (EBook, 2018, No Starch Press)

1 online resource (276 pages) : illustrations, 276 Seiten

Sprache: English

Am 2018 von No Starch Press veröffentlicht.

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"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 …

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Themen

  • Malware (Computer software)
  • Computer viruses.
  • Debugging in computer science.