Book Image

Machine Learning for Cybersecurity Cookbook

By : Emmanuel Tsukerman
Book Image

Machine Learning for Cybersecurity Cookbook

By: Emmanuel Tsukerman

Overview of this book

Organizations 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.
Table of Contents (11 chapters)

Malware dynamic analysis

Unlike static analysis, dynamic analysis is a malware analysis technique in which the expert executes the sample, and then studies the sample's behavior as it is being run. The main advantage of dynamic analysis over static is that it allows you to bypass obfuscation by simply observing how a sample behaves, rather than trying to decipher the sample's contents and behavior. Since malware is intrinsically unsafe, researchers resort to executing samples in a virtual machine (VM). This is called sandboxing.

Getting ready

One of the most prominent tools for automating the analysis of samples in a VM is Cuckoo Sandbox. The initial installation of Cuckoo Sandbox is straightforward; simply run the...