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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

Deep steganography

Steganography is the practice of hiding a message (that is, the secret) within another medium, such as a file, text, image, or video (that is, the cover). When the secret is embedded into the cover, the result is called the container. In this recipe, we will use deep neural networks to create the hiding and revealing processes. Unlike common steganographic methods, which encode the secret in the LSB of the cover, deep learning distributes the secret across all bits.

Getting ready

In this recipe, you will need access to a GPU.

How to do it…

  1. Clone...
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