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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

Assessing password security using ML

Password cracking is the systematic endeavor of discovering the password of a secure system. Cracking can involve using common passwords, cleverly generated candidate passwords (for example, replacing the letter O with the number 0 or writing a word backward), or just using a plain bruteforce exhaustive search. To make it more difficult to crack a password, a strong password must be chosen.

Getting ready

To prepare for this recipe, we need to install pandas, sklearn, and xgboost in pip. Use the following code to do so:

pip install pandas sklearn xgboost

In addition, extract the archived dataset, that is, PasswordDataset.7z.

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