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Hands-On Artificial Intelligence for Cybersecurity

You're reading from Hands-On Artificial Intelligence for Cybersecurity Implement smart AI systems for preventing cyber attacks and detecting threats and network anomalies

Product type Paperback

Published in Aug 2019

Publisher Packt

ISBN-13 9781789804027

Length 342 pages

Edition 1st Edition

Languages

Python

Concepts

Artificial Intelligence

Author (1):

Alessandro Parisi

View More author details

Table of Contents (16) Chapters

Preface

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

2. Introduction to AI for Cybersecurity Professionals FREE CHAPTER

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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Python libraries for cybersecurity

Python is not only one of the best languages for data science and AI, but also the language preferred by penetration testers and malware analysts (along with low-level languages, such as C and Assembly).

In Python, there are an infinite number of libraries ready for use, which simplify the daily activities of researchers.

Next, we will analyze some of the most common and the most used of them.

Pefile

The Pefile library is very useful for analyzing Windows executable files, especially during the phases of static malware analysis, looking for possible indications of compromise or the presence of malicious code in executables. In fact, Pefile makes it very easy to analyze the Portable Executable...

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Authors (1)

Parisi

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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