Book Image

Hands-On Artificial Intelligence for Cybersecurity

By : Alessandro Parisi
Book Image

Hands-On Artificial Intelligence for Cybersecurity

By: Alessandro Parisi

Overview of this book

Today's organizations spend billions of dollars globally on cybersecurity. Artificial intelligence has emerged as a great solution for building smarter and safer security systems that allow you to predict and detect suspicious network activity, such as phishing or unauthorized intrusions. This cybersecurity book presents and demonstrates popular and successful AI approaches and models that you can adapt to detect potential attacks and protect your corporate systems. You'll learn about the role of machine learning and neural networks, as well as deep learning in cybersecurity, and you'll also learn how you can infuse AI capabilities into building smart defensive mechanisms. As you advance, you'll be able to apply these strategies across a variety of applications, including spam filters, network intrusion detection, botnet detection, and secure authentication. By the end of this book, you'll be ready to develop intelligent systems that can detect unusual and suspicious patterns and attacks, thereby developing strong network security defenses using AI.
Table of Contents (16 chapters)
Free Chapter
1
Section 1: AI Core Concepts and Tools of the Trade
4
Section 2: Detecting Cybersecurity Threats with AI
8
Section 3: Protecting Sensitive Information and Assets
12
Section 4: Evaluating and Testing Your AI Arsenal

GANs in a nutshell

GANs were theorized in a famous paper that dates back to 2014 (https://arxiv.org/abs/1406.2661), written by a team of researchers including Ian Goodfellow and Yoshua Bengio, which described the potential and characteristics of a special category of adversarial processes, called GANs.

The basic idea behind GANs is simple, as they consist of putting two neural networks in competition with one another, until a balanced condition of results is achieved; however at the same time, the possibilities of using these intuitions are almost unlimited, since GANs are able to learn how to imitate and artificially reproduce any data distribution, whether it represents faces, voices, texts, or even works of art.

In this chapter, we will extend the use of GANs in the field of cybersecurity, learning how it is possible to use them to both carry out attacks (such as attacks against...