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Mastering Machine Learning for Penetration Testing

You're reading from   Mastering Machine Learning for Penetration Testing Develop an extensive skill set to break self-learning systems using Python

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Product type Paperback
Published in Jun 2018
Publisher Packt
ISBN-13 9781788997409
Length 276 pages
Edition 1st Edition
Languages
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Author (1):
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Chiheb Chebbi Chiheb Chebbi
Author Profile Icon Chiheb Chebbi
Chiheb Chebbi
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Table of Contents (13) Chapters Close

Preface 1. Introduction to Machine Learning in Pentesting FREE CHAPTER 2. Phishing Domain Detection 3. Malware Detection with API Calls and PE Headers 4. Malware Detection with Deep Learning 5. Botnet Detection with Machine Learning 6. Machine Learning in Anomaly Detection Systems 7. Detecting Advanced Persistent Threats 8. Evading Intrusion Detection Systems 9. Bypassing Machine Learning Malware Detectors 10. Best Practices for Machine Learning and Feature Engineering 11. Assessments 12. Other Books You May Enjoy

Botnet Detection with Machine Learning

Nowadays, connected devices play an important role in modern life. From smart home appliances, computers, coffee machines, and cameras, to connected cars, this huge shift in our lifestyles has made our lives easier. Unfortunately, these exposed devices could be attacked and accessed by attackers and cyber criminals who could use them later to enable larger-scale attacks. Security vendors provide many solutions and products to defend against botnets, but in this chapter, as we did in previous chapters, we are going to learn how to build novel botnet detection systems with Python and machine learning techniques.

In this chapter, we will see:

  • An overview of botnets
  • How to build a botnet detector with different machine learning algorithms
  • How to build a Twitter bot detector
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