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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

Introduction to Machine Learning in Pentesting

Currently, machine learning techniques are some of the hottest trends in information technology. They impact every aspect of our lives, and they affect every industry and field. Machine learning is a cyber weapon for information security professionals. In this book, readers will not only explore the fundamentals behind machine learning techniques, but will also learn the secrets to building a fully functional machine learning security system. We will not stop at building defensive layers; we will illustrate how to build offensive tools to attack and bypass security defenses. By the end of this book, you will be able to bypass machine learning security systems and use the models constructed in penetration testing (pentesting) missions.

In this chapter, we will cover:

  • Machine learning models and algorithms
  • Performance evaluation metrics
  • Dimensionality reduction
  • Ensemble learning
  • Machine learning development environments and Python libraries
  • Machine learning in penetration testing – promises and challenges
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