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Machine Learning for Cybersecurity Cookbook
book

Machine Learning for Cybersecurity Cookbook

by Emmanuel Tsukerman
November 2019
Intermediate to advanced content levelIntermediate to advanced
346 pages
9h 36m
English
Packt Publishing
Content preview from Machine Learning for Cybersecurity Cookbook

Building a dynamic malware classifier

In certain situations, there is a considerable advantage to being able to detect malware based on its behavior. In particular, it is much more difficult for a malware to hide its intentions when it is being analyzed in a dynamic situation. For this reason, classifiers that operate on dynamic information can be much more accurate than their static counterparts. In this section, we provide a recipe for a dynamic malware classifier. The dataset we use is part of a VirusShare repository from android applications. The dynamic analysis was performed by Johannes Thon on several LG Nexus 5 devices with Android API 23, (over 4,000 malicious apps were dynamically analyzed on the LG Nexus 5 device farm (API 23), ...

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Publisher Resources

ISBN: 9781789614671Supplemental Content