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

Getting to know Python for AI and cybersecurity

Among all the languages ​​that can be used to program AI tools and algorithms, Python is the one that, in recent years, has shown to be constantly growing and is appreciated by programmers, new and old. Despite the competition being fierce, as languages ​​such as R, as well as Java, can boast tens of thousands of developers in their ranks, Python has gained the reputation of being a language of choice not only for data science but also (and above all) for machine learning (ML), deep learning (DL), and more generally, for the development of artificial intelligence (AI) algorithms.

The success of Python in these areas should not be surprising. Python was originally developed for programming numerical calculations, but was then extended to non-specialist areas, assuming the form of a general-purpose programming...