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Mastering Machine Learning for Penetration Testing

More Information
Learn
  • Take an in-depth look at machine learning
  • Get to know natural language processing (NLP)
  • Understand malware feature engineering
  • Build generative adversarial networks using Python libraries
  • Work on threat hunting with machine learning and the ELK stack
  • Explore the best practices for machine learning
About

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.

Features
  • Identify ambiguities and breach intelligent security systems
  • Perform unique cyber attacks to breach robust systems
  • Learn to leverage machine learning algorithms
Page Count 276
Course Length 8 hours 16 minutes
ISBN9781788997409
Date Of Publication 26 Jun 2018

Authors

Chiheb Chebbi

Chiheb Chebbi is an InfoSec enthusiast who has experience in various aspects of information security, focusing on the investigation of advanced cyber attacks and researching cyber espionage and APT attacks. Chiheb is currently pursuing an engineering degree in computer science at TEK-UP university in Tunisia.

His core interests are infrastructure penetration testing, deep learning, and malware analysis. In 2016, he was included in the Alibaba Security Research Center Hall Of Fame. His talk proposals were accepted by DeepSec 2017, Blackhat Europe 2016, and many world-class information security conferences.