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

Knocking Down CAPTCHAs

CAPTCHA is short for Completely Automated Public Turing test to tell Computers and Humans Apart. These are tests that verify whether a computing system is being operated by a human or a robot.

CAPTCHAs were built in such a way that they would need human mediation to be administered to computing systems as a part of the authentication system to ensure system security and hence prevention of unwanted looses for organizations.

Apart from summarizing how CAPTCHA works, this chapter also covers the following topics:

  • Characteristics of CAPTCHAs
  • Using artificial intelligence to crack CAPTCHAs
  • Types of CAPTCHA
  • Solving CAPTCHAs with neural networks

The following screenshot shows a CAPTCHA image that is used for verification: