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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

Concepts

Machine Learning

Author (1):

Emmanuel Tsukerman

Table of Contents (11) Chapters

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

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Appendix

Facial recognition

A facial recognition system is a technology for identifying or verifying a person in images or videos. When performing OSINT on a target or potential targets, a facial recognition system can be invaluable. In this recipe, you will learn how to use the well-developed face_recognition Python library.

Getting ready

Preparation for this recipe consists of installing the face_recognition and OpenCV packages in pip. The instructions are as follows:

pip install face_recognition opencv-python

In addition, you will want a portrait of an individual and a collection of images through which you would like to search for that individual.

...

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Authors (1)

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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