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Mastering Machine Learning for Penetration Testing

You're reading from   Mastering Machine Learning for Penetration Testing Develop an extensive skill set to break self-learning systems using Python

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Product type Paperback
Published in Jun 2018
Publisher Packt
ISBN-13 9781788997409
Length 276 pages
Edition 1st Edition
Languages
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Author (1):
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Chiheb Chebbi Chiheb Chebbi
Author Profile Icon Chiheb Chebbi
Chiheb Chebbi
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Table of Contents (13) Chapters Close

Preface 1. Introduction to Machine Learning in Pentesting 2. Phishing Domain Detection FREE CHAPTER 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

Bypassing Machine Learning Malware Detectors

In the previous chapter, you learned that you can break into machine learning models and make them perform malicious activities by using adversarial machine learning techniques. In this chapter, we are going to explore further techniques, like how to fool artificial neural networks and deep learning networks. We are going to look at anti-malware system evasion as a case study.

In this chapter, we will cover the following:

  • Adversarial deep learning
  • How to bypass next generation malware detectors with generative adversarial networks
  • Bypassing machine learning with reinforcement learning
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