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Hands-On Artificial Intelligence for Cybersecurity

You're reading from Hands-On Artificial Intelligence for Cybersecurity

Product type Book

Published in Aug 2019

Publisher Packt

ISBN-13 9781789804027

Pages 342 pages

Edition 1st Edition

Languages

Concepts

Artificial Intelligence

Author (1):

Alessandro Parisi

Table of Contents (16) Chapters

Preface

1. Section 1: AI Core Concepts and Tools of the Trade

2. Introduction to AI for Cybersecurity Professionals

3. Setting Up Your AI for Cybersecurity Arsenal

4. Section 2: Detecting Cybersecurity Threats with AI

5. Ham or Spam? Detecting Email Cybersecurity Threats with AI

6. Malware Threat Detection

7. Network Anomaly Detection with AI

8. Section 3: Protecting Sensitive Information and Assets

9. Securing User Authentication

10. Fraud Prevention with Cloud AI Solutions

11. GANs - Attacks and Defenses

12. Section 4: Evaluating and Testing Your AI Arsenal

13. Evaluating Algorithms

14. Assessing your AI Arsenal

15. Other Books You May Enjoy

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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...

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Authors (1)

Alessandro Parisi

Alessandro Parisi has been an IT professional for over 20 years, acquiring significant experience as a Security Data Scientist, and as an Artificial Intelligence Cybersecurity and Blockchain specialist. He has experience of operating within organizational and decisional contexts characterized by high complexity. Over the years, he has helped companies to adopt Artificial Intelligence and Blockchain DLT technologies as strategic tools in protecting sensitive corporate assets. He holds a Master Degree in Economics and Statistics.

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