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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

Malware is one of the most prevalent cyber threats haunting the security of modern organizations. Black hat hackers are constantly improving; hence, classic detection techniques are obsolete, and AV products are often unable to detect advanced persistent threats. That is why machine learning techniques can help us to detect malware.

In this chapter, we learned how to build malware classifiers, using many machine learning algorithms and open source Python libraries. The next chapter will teach us how to build more robust systems to detect malware, using the same algorithm used by the human mind. We are going to learn how to use deep learning to detect malware , using the same Python libraries used throughout this book.

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