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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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Predictive analytics for credit card fraud detection

To adequately address the problem of fraud detection, it is necessary to develop predictive analytics models, that is, mathematical models that can identify trends within the data, using a data-driven approach.

Unlike descriptive analytics (whose paradigm is constituted by business intelligence (BI)), which limits itself to classifying the past data on the basis of measures deriving from the application of descriptive statistics (such as sums, averages, variances, and so on), precisely describe the characteristics of the data being analyzed; instead, by looking at the present and past situation, predictive analytics tries to project itself in order to predict future events with a certain degree of probability. It does this by extrapolating hidden patterns within the analyzed data.

Being data-driven, predictive analytics makes...

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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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