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Mastering Machine Learning for Penetration Testing

Mastering Machine Learning for Penetration Testing

By : Chiheb Chebbi
4 (4)
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Mastering Machine Learning for Penetration Testing

Mastering Machine Learning for Penetration Testing

4 (4)
By: Chiheb Chebbi

Overview of this book

Cyber security is crucial for both businesses and individuals. As systems are getting smarter, we now see machine learning interrupting computer security. With the adoption of machine learning in upcoming security products, it’s important for pentesters and security researchers to understand how these systems work, and to breach them for testing purposes. This book begins with the basics of machine learning and the algorithms used to build robust systems. Once you’ve gained a fair understanding of how security products leverage machine learning, you'll dive into the core concepts of breaching such systems. Through practical use cases, you’ll see how to find loopholes and surpass a self-learning security system. As you make your way through the chapters, you’ll focus on topics such as network intrusion detection and AV and IDS evasion. We’ll also cover the best practices when identifying ambiguities, and extensive techniques to breach an intelligent system. By the end of this book, you will be well-versed with identifying loopholes in a self-learning security system and will be able to efficiently breach a machine learning system.
Table of Contents (13 chapters)
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Summary

Malware is one of the most prevalent cyber threats haunting the security of modern organizations. Black hat hackers are constantly improving; hence, classic detection techniques are obsolete, and AV products are often unable to detect advanced persistent threats. That is why machine learning techniques can help us to detect malware.

In this chapter, we learned how to build malware classifiers, using many machine learning algorithms and open source Python libraries. The next chapter will teach us how to build more robust systems to detect malware, using the same algorithm used by the human mind. We are going to learn how to use deep learning to detect malware , using the same Python libraries used throughout this book.

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