Book Image

Hands-On Artificial Intelligence for Cybersecurity

By : Parisi
Book Image

Hands-On Artificial Intelligence for Cybersecurity

By: 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

Advanced malware detection with deep learning

In the last part of the chapter, we will introduce—for the sake of completeness—some solutions of malware detection that make use of experimental methodologies based on neural networks.

We will have a more in-depth look at the topic of deep learning techniques later on in Chapter 8, GANS – Attacks and Defenses (especially when we will talk about Generative Adversarial Networks (GANs)).

Here, we will introduce the topic to show an innovative and unconventional approach to the problem of the classification of different families of malware, which makes use of deep learning algorithms developed in a completely different field of research, such as that of image recognition using Convolutional Neural Networks (CNNs).

But before going into that, let's briefly introduce Neural Networks (NNs) and their main features...