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Malware Data Science: Attack Detection and Attribution

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Description: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 - 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 visualizationWhether 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.We have made it easy for you to find a PDF Ebooks without any digging. And by having access to our ebooks online or by storing it on your computer, you have convenient answers with Malware Data Science: Attack Detection and Attribution. To get started finding Malware Data Science: Attack Detection and Attribution, you are right to find our website which has a comprehensive collection of manuals listed.
Our library is the biggest of these that have literally hundreds of thousands of different products represented.

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Format: PDF, EPUB & Kindle Edition

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ISBN: 1593278608

Description: 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 - 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 visualizationWhether 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.We have made it easy for you to find a PDF Ebooks without any digging. And by having access to our ebooks online or by storing it on your computer, you have convenient answers with Malware Data Science: Attack Detection and Attribution. To get started finding Malware Data Science: Attack Detection and Attribution, you are right to find our website which has a comprehensive collection of manuals listed.
Our library is the biggest of these that have literally hundreds of thousands of different products represented.

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Malware Data Science: Attack Detection and Attribution

Malware Data Science: Attack Detection and Attribution

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