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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 FREE CHAPTER 2. Machine Learning-Based Malware Detection 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

ML-based steganalysis

One of the main techniques in steganography is hiding messages in images by altering the least significant bits (LSB) of the pixels with those of the message bits. The result is an image with a message hidden in it that the human eye cannot distinguish from the original image. This is because, on changing the LSB in the pixels of an image, the pixel values are only altered by a small amount, resulting in a visually similar image.

There are two prominent methods for LSB:

  • The naïve method is called LSB replacement. In this method, the LSB bit remains unchanged if the message bit is the same as the LSB; otherwise, the bit is altered. Hence, the odd pixels are reduced by 1 in intensity, whereas the even pixel values are incremented by 1. However, this causes an imbalance in the image histogram, which can be easily detected by statistical methods for steganalysis...
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