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With the proliferation of information technologies and data among us, cybersecurity has become a necessity. Machine learning helps organisations by getting insights from raw data, predicting future outcomes and more.

For a few years now, such utilisation of machine learning techniques has been started being implemented in cybersecurity. It helps in several ways, including identifying frauds, malicious codes and other such.

In this article, we list down the top eight books, in no particular order, on machine learning In cybersecurity that one must-read.

About: Written by Sumeet Dua and Xian Du, this book introduces the basic notions in machine learning and data mining. It provides a unified reference for specific machine learning solutions to cybersecurity problems as well as provides a foundation in cybersecurity fundamentals, including surveys of contemporary challenges.

The book details some of the cutting-edge machine learning and data mining techniques that can be used in cybersecurity, such as in-depth discussions of machine learning solutions to detection problems, contemporary cybersecurity problems, categorising methods for detecting, scanning, and profiling intrusions and anomalies, among others.

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About: In Malware Data Science, security data scientist Joshua Saxe introduces machine learning, statistics, social network analysis, and data visualisation, and shows you how to apply these methods to malware detection and analysis.

Youll learn how to analyse malware using static analysis, identify adversary groups through shared code analysis, detect vulnerabilities by building machine learning detectors, identify malware campaigns, trends, and relationships through data visualisation, etc.

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About: This book begins with an introduction of machine learning and algorithms that are used to build AI systems. After gaining a fair understanding of how security products leverage machine learning, you will learn the core concepts of breaching the AI and ML systems.

With the help of hands-on cases, you will understand how to find loopholes as well as surpass a self-learning security system. After completing this book, readers will be able to identify the loopholes in a self-learning security system and will also be able to breach a machine learning system efficiently.

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About: In this book, youll learn how to use popular Python libraries such as TensorFlow, Scikit-learn, etc. to implement the latest AI techniques and manage difficulties faced by the cybersecurity researchers.

The book will lead you through classifiers as well as features for malware, which will help you to train and test on real samples. You will also build self-learning, reliant systems to handle the cybersecurity tasks such as identifying malicious URLs, spam email detection, intrusion detection, tracking user and process behaviour, among others.

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About: This book is for the data scientists, machine learning developers, security researchers, and anyone keen to apply machine learning to up-skill computer security. In this book, you will learn how to use machine learning algorithms with complex datasets to implement cybersecurity concepts, implement machine learning algorithms such as clustering, k-means, and Naive Bayes to solve real-world problems, etc.

You will also learn how to speed up a system using Python libraries with NumPy, Scikit-learn, and CUDA, combat malware, detect spam and fight financial fraud to mitigate cybercrimes, among others.

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About: This book teaches you how to use machine learning for penetration testing. You will learn a hands-on and practical manner, how to use the machine learning to perform penetration testing attacks, and how to perform penetration testing attacks on machine learning systems. You will also learn the techniques that few hackers or security experts know about.

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About: In this book, you will learn machine learning in cybersecurity self-assessment, how to identify and describe the business environment in cybersecurity projects using machine learning, etc.

The book covers all machine learning in cybersecurity essentials, such as extensive criteria grounded in the past and current successful projects and activities by experienced machine learning in cybersecurity practitioners, among others.

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About: This book presents a collection of state-of-the-art AI approaches to cybersecurity and cyber threat intelligence. It offers strategic defence mechanisms for malware, addressing cybercrime, and assessing vulnerabilities to yield proactive rather than reactive countermeasures.

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Original post:
Top 8 Books on Machine Learning In Cybersecurity One Must Read - Analytics India Magazine