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

IDS evasion via GAN

We have dealt extensively with IDS in Chapter 5, Network Anomaly Detection with AI, where we learned about the delicate role played by these devices in a context like the current one, characterized by a growing explosion of malware threats spread through network attacks.

It is therefore necessary to introduce tools capable of promptly detecting possible malware threats, preventing them from spreading across the entire corporate network, and thereby compromising both the software and the integrity of the data (just think, for example, of the growing diffusion of ransomware attacks).

In order to be able to promptly and effectively carry out—that is, reduce—the number of false positives, it is therefore necessary to equip IDS systems with automated procedures capable of adequately classifying the traffic analyzed. It is no coincidence, therefore...