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

Installing DL libraries

In this section, we will consider the advantages of installing some of the main Python libraries for AI, in particular, to exploit the potential of deep learning.

The libraries that we will cover are as follows:

  • TensorFlow
  • Keras
  • PyTorch

Prior to discovering the advantages of the individual libraries and proceeding with their installation, let's spend a few words on the advantages and characteristics of deep learning for cybersecurity.

Deep learning pros and cons for cybersecurity

One of the distinctive features of deep learning, compared to other branches of AI, is the ability to exploit general-purpose algorithms, by leveraging neural networks. In this way, it is possible to face similar problems...