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Machine Learning for Cybersecurity Cookbook

You're reading from  Machine Learning for Cybersecurity Cookbook

Product type Book
Published in Nov 2019
Publisher Packt
ISBN-13 9781789614671
Pages 346 pages
Edition 1st Edition
Languages
Author (1):
Emmanuel Tsukerman Emmanuel Tsukerman
Profile icon Emmanuel Tsukerman
Toc

Table of Contents (11) Chapters close

Preface 1. Machine Learning for Cybersecurity 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

Deep learning for password cracking

Modern password cracking tools, such as John the Ripper, allow a hacker to test billions of potential passwords in a matter of seconds. Not only do such tools allow a hacker to try out every password in a dictionary of common passwords, but they can also automatically transform these passwords by using concatenation (for example, password1234), leetspeak (p4s5w0rd), and other promising techniques. Though these techniques are promising, finding additional promising transformations is a difficult task. The ML system known as PassGAN uses a generative adversarial network (GAN) to automatically learn such rules by observing large datasets of real passwords (gathered from a corpus of actual password leaks) and to generate high-probability password candidates. In this recipe, you will train PassGAN on a corpus of leaked passwords and use it to generate...

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