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Description of  Machine Learning for Cybersecurity Cookbook

1789614678 epub Learn how to apply modern AI to create powerful cybersecurity solutions for malware, pentesting, social engineering, data privacy, and intrusion detectionKey FeaturesManage data of varying complexity to protect your system using the Python ecosystem Manage data of varying complexity to protect your system using the Python ecosystem Apply ML to pentesting, malware, data privacy, intrusion detection system(IDS) and social engineering Apply ML to pentesting, malware, data privacy, intrusion detection system(IDS) and social engineering Automate your daily workflow by addressing various security challenges using the recipes covered in the bookAutomate your daily workflow by addressing various security challenges using the recipes covered in the bookBook DescriptionOrganizations today face a major threat in terms of cybersecurity, from malicious URLs to credential reuse, and having robust security systems can make all the difference. With this book, you'll learn how to use Python libraries such as TensorFlow and scikit-learn to implement the latest artificial intelligence (AI) techniques and handle challenges faced by cybersecurity researchers. You'll begin by exploring various machine learning (ML) techniques and tips for setting up a secure lab environment. Next, you'll implement key ML algorithms such as clustering, gradient boosting, random forest, and XGBoost. The book will guide you through constructing classifiers and features for malware, which you'll train and test on real samples. As you progress, you'll build self-learning, reliant systems to handle cybersecurity tasks such as identifying malicious URLs, spam email detection, intrusion detection, network protection, and tracking user and process behavior. Later, you'll apply generative adversarial networks (GANs) and autoencoders to advanced security tasks. Finally, you'll delve into secure and private AI to protect the privacy rights of consumers using your ML models. By the end of this book, you'll have the skills you need to tackle real-world problems faced in the cybersecurity domain using a recipe-based approach. What you will learnLearn how to build malware classifiers to detect suspicious activities Learn how to build malware classifiers to detect suspicious activities Apply ML to generate custom malware to pentest your security Apply ML to generate custom malware to pentest your security Use ML algorithms with complex datasets to implement cybersecurity concepts Use ML algorithms with complex datasets to implement cybersecurity concepts Create neural networks to identify fake videos and images Create neural networks to identify fake videos and images Secure your organization from one of the most popular threats – insider threats Secure your organization from one of the most popular threats – insider threats Defend against zero-day threats by constructing an anomaly detection system Defend against zero-day threats by constructing an anomaly detection system Detect web vulnerabilities effectively by combining Metasploit and ML Detect web vulnerabilities effectively by combining Metasploit and ML Understand how to train a model without exposing the training dataUnderstand how to train a model without exposing the training dataWho this book is forThis book is for cybersecurity professionals and security researchers who are looking to implement the latest machine learning techniques to boost computer security, and gain insights into securing an organization using red and blue team ML. This recipe-based book will also be useful for data scientists and machine learning developers who want to experiment with smart techniques in the cybersecurity domain. Working knowledge of Python programming and familiarity with cybersecurity fundamentals will help you get the most out of this book.Table of ContentsMachine Learning for CybersecurityMachine Learning for CybersecurityMachine Learning-Based Malware DetectionMachine Learning-Based Malware DetectionAdvanced Malware DetectionAdvanced Malware DetectionMachine Learning for Social EngineeringMachine Learning for Social EngineeringPenetration Testing Using Machine LearningPenetration Testing Using Machine LearningAutomatic Intrusion DetectionAutomatic Intrusion DetectionSecuring and Attacking Data with Machine LearningSecuring and Attacking Data with Machine LearningSecure and Private AISecure and Private AIAppendixAppendix