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Mastering Machine Learning for Penetration Testing

You're reading from  Mastering Machine Learning for Penetration Testing

Product type Book
Published in Jun 2018
Publisher Packt
ISBN-13 9781788997409
Pages 276 pages
Edition 1st Edition
Languages
Author (1):
Chiheb Chebbi Chiheb Chebbi
Profile icon Chiheb Chebbi
Toc

Table of Contents (13) Chapters close

Preface 1. Introduction to Machine Learning in Pentesting 2. Phishing Domain Detection 3. Malware Detection with API Calls and PE Headers 4. Malware Detection with Deep Learning 5. Botnet Detection with Machine Learning 6. Machine Learning in Anomaly Detection Systems 7. Detecting Advanced Persistent Threats 8. Evading Intrusion Detection Systems 9. Bypassing Machine Learning Malware Detectors 10. Best Practices for Machine Learning and Feature Engineering 11. Assessments 12. Other Books You May Enjoy

Summary

Now we have learned the most commonly used machine learning techniques; before diving into practical labs, we need to acquire a fair understanding of how these models actually work. Our practical experience will start from the next chapter.

After reading this chapter, I assume that we can build our own development environment. The second chapter will show us what it takes to defend against advanced, computer-based, social engineering attacks, and we will learn how to build a smart phishing detector. Like in every chapter, we will start by learning the techniques behind the attacks, and we will walk through the practical steps in order to build a phishing detecting system.

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Mastering Machine Learning for Penetration Testing
Published in: Jun 2018 Publisher: Packt ISBN-13: 9781788997409
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