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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

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Product type Paperback
Published in Aug 2019
Publisher Packt
ISBN-13 9781789804027
Length 342 pages
Edition 1st Edition
Languages
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Author (1):
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Alessandro Parisi Alessandro Parisi
Author Profile Icon Alessandro Parisi
Alessandro Parisi
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Table of Contents (16) Chapters Close

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

Phishing detection with logistic regression and decision trees

After having analyzed the Perceptron and the SVM, we now deal with alternative classification strategies that make use of logistic regression and decision trees.

But before continuing, we will discover the distinctive features of these algorithms and their use for spam detection and phishing, starting with regression models.

Regression models

Regression models are undoubtedly the most used of all learning algorithms. Developed from statistical analysis, regression models have quickly spread in ML and in AI in general. The most known and used regression model is linear regression, thanks to the simplicity of its implementation and the good predictive capacity that...

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