Book Image

Hands-On Machine Learning for Cybersecurity

By : Soma Halder, Sinan Ozdemir
Book Image

Hands-On Machine Learning for Cybersecurity

By: Soma Halder, Sinan Ozdemir

Overview of this book

Cyber threats today are one of the costliest losses that an organization can face. In this book, we use the most efficient tool to solve the big problems that exist in the cybersecurity domain. The book begins by giving you the basics of ML in cybersecurity using Python and its libraries. You will explore various ML domains (such as time series analysis and ensemble modeling) to get your foundations right. You will implement various examples such as building system to identify malicious URLs, and building a program to detect fraudulent emails and spam. Later, you will learn how to make effective use of K-means algorithm to develop a solution to detect and alert you to any malicious activity in the network. Also learn how to implement biometrics and fingerprint to validate whether the user is a legitimate user or not. Finally, you will see how we change the game with TensorFlow and learn how deep learning is effective for creating models and training systems
Table of Contents (13 chapters)
Free Chapter
Basics of Machine Learning in Cybersecurity
Using Data Science to Catch Email Fraud and Spam

Segregating Legitimate and Lousy URLs

A recent study showed that 47% of the world's population is online right now. With the World Wide Web (WWW) at our disposal, we find ourselves fiddling with the various internet sites on offer. However, this exposes us to the most dangerous threat of all, because we are not able distinguish between a legitimate URL and a malicious URL.

In this chapter, we will use a machine learning approach to easily tell the difference between benign and malicious URLs. This chapter will cover the following topics:

  • Understanding URLs and how they fit in the internet address scheme
  • Introducing malicious URLs
  • Looking at the different ways malicious URLs propagate
  • Using heuristics to detect malicious URLs
  • Using machine learning to detect malicious URLs

A URL stands for uniform resource locator. A URL is essentially the address of a web page located in...