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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

Product type Paperback

Published in Nov 2019

Publisher Packt

ISBN-13 9781789614671

Length 346 pages

Edition 1st Edition

Languages

Python

Tools

Metasploit

Concepts

Cybersecurity

Author (1):

Emmanuel Tsukerman

View More author details

Table of Contents (11) Chapters

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

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Appendix

Featurizing PDF files

In this section, we will see how to featurize PDF files in order to use them for machine learning. The tool we will be utilizing is the PDFiD Python script designed by Didier Stevens (https://blog.didierstevens.com/). Stevens selected a list of 20 features that are commonly found in malicious files, including whether the PDF file contains JavaScript or launches an automatic action. It is suspicious to find these features in a file, hence, the appearance of these can be indicative of malicious behavior.

Essentially, the tool scans through a PDF file, and counts the number of occurrences of each of the ~20 features. A run of the tool appears as follows:

 PDFiD 0.2.5 PythonBrochure.pdf

 PDF Header: %PDF-1.6
 obj                 1096
 endobj              1095
 stream              1061
 endstream           1061
 xref                   0
 trailer                0
 startxref...

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Authors (1)

Emmanuel Tsukerman

Emmanuel Tsukerman

Emmanuel Tsukerman graduated from Stanford University and obtained his Ph.D. from UC Berkeley. In 2017, Dr. Tsukerman's anti-ransomware product was listed in the Top 10 ransomware products of 2018 by PC Magazine. In 2018, he designed an ML-based, instant-verdict malware detection system for Palo Alto Networks' WildFire service of over 30,000 customers. In 2019, Dr. Tsukerman launched the first cybersecurity data science course.

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