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

Introduction to the types of abnormalities in URLs

Lousy URLs are URLs that have been created with malicious intent. They are often the precursors to cyberattacks that may happen in the near future. Lousy URLs can hit pretty close to home, leaving each one of us very vulnerable to bad sites that we might visit on purpose or by accident.

Google often has inbuilt malicious URL detection capabilities, and the following screenshot shows what many of us have bumped into upon detecting a malicious URL:

Malicious URLs lead us to bad websites that either try to sell us counterfeit products, such as medication, unsolicited products, such as watches from Rolex, and so on. These websites might sell a variety of items, such as screensavers for your computer and funny pictures.

Bad URLs may also lead to phishing sites—that is, sites that imitate real websites, such as banks and credit...