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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

Detecting Advanced Persistent Threats

Modern organizations face cyber threats on a daily basis. Black hat hackers do not show any indication that they are going to stop. New hacking techniques appear regularly. Detecting advanced persistent threats (APTs) is a hard mission, since the goals of these attacks are to stay undetected for a long period of time, and to steal data, rather than cause damage to systems.

According to multiple information security reports, the number of APT attacks is increasing in a notable way, targeting national defenses, manufacturing, and the financial industry. Thus, classic protection techniques are, in many cases, useless. Deploying suitable platforms and solutions can help organizations and companies defend against cyber attacks, especially APTs.

This chapter will give you step-by-step guidance to teach you how to build a threat-hunting platform...

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