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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

Measuring the similarity between two strings

To check whether two files are identical, we utilize standard cryptographic hash functions, such as SHA256 and MD5. However, at times, we would like to also know to what extent two files are similar. For that purpose, we utilize similarity hashing algorithms. The one we will be demonstrating here is ssdeep.

First, let's see how to use ssdeep to compare two strings. This can be useful to detect tampering in a text or script and also plagiarism.

Getting ready

Preparation for this recipe consists of installing the ssdeep package in pip. The installation is a little tricky and does not always work on Windows. Instructions can be found at https://python-ssdeep.readthedocs.io...

You have been reading a chapter from
Machine Learning for Cybersecurity Cookbook
Published in: Nov 2019
Publisher: Packt
ISBN-13: 9781789614671
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