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Hands-On Artificial Intelligence for Cybersecurity

Hands-On Artificial Intelligence for Cybersecurity

By : Parisi
4.4 (5)
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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)
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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

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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