Sign In Start Free Trial
Account

Add to playlist

Create a Playlist

Modal Close icon
You need to login to use this feature.
  • Hands-On Artificial Intelligence for Cybersecurity
  • Toc
  • feedback
Hands-On Artificial Intelligence for Cybersecurity

Hands-On Artificial Intelligence for Cybersecurity

By : Parisi
4.4 (5)
close
Hands-On Artificial Intelligence for Cybersecurity

Hands-On Artificial Intelligence for Cybersecurity

4.4 (5)
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)
close
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

Summary

This chapter has illustrated the different techniques that can be used to increase the effectiveness of user authentication procedures and to promptly detect the possible presence of compromised user accounts.

These techniques are based on the use of biometric evidence, such as facial recognition, or biometric behavior, such as keyboard dynamics, which can be implemented using AI algorithms that exploit neural networks, such as MLP.

We have also seen how to reduce the dimensionality of the data to their main components by using PCA.

Finally, the advantages and disadvantages associated with the use of biometric evidence for user authentication and recognition were highlighted.

In the next chapter, we will learn about fraud prevention using cloud AI solutions.

Unlock full access

Continue reading for free

A Packt free trial gives you instant online access to our library of over 7000 practical eBooks and videos, constantly updated with the latest in tech
bookmark search playlist download font-size

Change the font size

margin-width

Change margin width

day-mode

Change background colour

Close icon Search
Country selected

Close icon Your notes and bookmarks

Delete Bookmark

Modal Close icon
Are you sure you want to delete it?
Cancel
Yes, Delete