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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 2. Phishing Domain Detection FREE CHAPTER 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 overview

Botnet is a combination of the two terms bot and net. The bot part represents the fact that this malware automates things and tasks like a robot. The second part refers to a network, in other words, a network of compromised devices. So, by definition, a botnet is a form of malware that attacks computers on the internet and controls them with command and control servers to perform a wide variety of automated tasks, including sending spam emails and performing Distributed Denial of Service (DDoS) attacks. Attacked machines join an immense network of compromised machines. One of the most notable botnets in previous years was the Mirai botnet. Mirai means the future in Japanese. This botnet hit millions of online devices, especially Internet of Things (IoT) appliances, by scanning and identifying vulnerable machines, taking advantage of the fact that most of them are...

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