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)

Keystroke dynamics

Keystroke dynamics, aka typing biometrics, is the study of recognizing a person by the way they type. One important use case is recognizing which user is logging in using a given credential, for example, who is logging in as root? Another use case is recognizing when a different user has typed a sequence of keystrokes. In this recipe, we'll show how to use a machine learning-based keystroke dynamics algorithm.

Getting ready

This recipe will require a Linux virtual or real machine. In preparation, do the following:

  1. Install git on your device.

In a Terminal, run the following command:

sudo apt install git
  1. Clone the git repository containing the code for the keystroke dynamics algorithm:
git clone...