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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

Deanonymizing Tor using machine learning

Tor is a free, open source software for enabling anonymous communication. In addition, websites accessible only when using the Tor browser exist, and are part of the dark web ecosystem – the name given to the part of the internet that is hidden from the average user. In this recipe, we will deanonymize Tor traffic by collecting enough features and information from individual sessions to be able to identify the activity of anonymized users. This recipe utilizes the conmarap/website-fingerprinting repository.

Getting ready

You will now be guided through the steps needed to set up Tor and the Lynx web browser:

  1. Set up an Ubuntu VM.
  2. Install git in the Terminal by running the...
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