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Machine Learning for Cybersecurity Cookbook

You're reading from   Machine Learning for Cybersecurity Cookbook Over 80 recipes on how to implement machine learning algorithms for building security systems using Python

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Product type Paperback
Published in Nov 2019
Publisher Packt
ISBN-13 9781789614671
Length 346 pages
Edition 1st Edition
Languages
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Author (1):
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Emmanuel Tsukerman Emmanuel Tsukerman
Author Profile Icon Emmanuel Tsukerman
Emmanuel Tsukerman
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Table of Contents (11) Chapters Close

Preface 1. Machine Learning for Cybersecurity 2. Machine Learning-Based Malware Detection FREE CHAPTER 3. Advanced Malware Detection 4. Machine Learning for Social Engineering 5. Penetration Testing Using Machine Learning 6. Automatic Intrusion Detection 7. Securing and Attacking Data with Machine Learning 8. Secure and Private AI 9. Other Books You May Enjoy Appendix

Securing and Attacking Data with Machine Learning

In this chapter, we will learn how to employ machine learning (ML) to secure and attack data. We will cover how to assess the strength of a password using ML, and conversely, how to crack passwords using deep learning. Similarly, we will cover how to hide messages in plain sight using steganography, as well as how to detect steganography using ML. In addition, we will apply ML with hardware security to attack physically unclonable functions (PUFs) using AI.

In this chapter, we will cover the following recipes:

  • Assessing password security using ML
  • Deep learning for password cracking
  • Deep steganography
  • ML-based steganalysis
  • ML attacks on PUFs
  • Encryption using deep learning
  • HIPAA data breaches – data exploration and visualization
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