10 Machine Learning Blueprints You Should Know for Cybersecurity: Protect your systems and boost your defenses

This book is for machine learning practitioners interested in applying their skills to solve cybersecurity issues. Cybersecurity workers looking to leverage ML methods will also find this book useful. An understanding of the fundamental machine learning concepts and beginner-level knowledge of Python programming are needed to grasp the concepts in this book. Whether you're a beginner or an experienced professional, this book offers a unique and valuable learning experience that'll help you develop the skills needed to protect your network and data against the ever-evolving threat landscape.
Table of Contents

On Cybersecurity and Machine Learning
Detecting Suspicious Activity
Malware Detection Using Transformers and BERT
Detecting Fake Reviews
Detecting Deepfakes
Detecting Machine-Generated Text
Attributing Authorship and How to Evade it
Detecting Fake News with Graph Neural Networks
Attacking Models with Adversarial Machine Learning
Protecting User Privacy with Differential Privacy
Protecting User Privacy with Federated Machine Learning
Breaking into the Sec-ML Industry