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

Malware Threat Detection

The high diffusion of malware and ransomware codes, together with the rapid polymorphic mutation in the different variants (polymorphic and metamorphic malware) of the same threats, has made traditional detection solutions based on signatures and hashing of image files obsolete, on which most common antivirus software is based.

It is therefore increasingly necessary to resort to machine learning (ML) solutions that allow a rapid screening (triage) of threats, focusing attention on not wasting scarce resources such as a malware analyst's skills and efforts.

This chapter will cover the following topics:

  • Introducing the malware analysis methodology
  • How to tell different malware families apart
  • Decision tree malware detectors
  • Detecting metamorphic malware with Hidden Markov Models (HMMs)
  • Advanced malware detection with deep learning
...