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


In this chapter, we have gone through the basics of machine learning. We briefly discussed how machine learning fits into daily use cases and its relationship with the cybersecurity world. We also learned the different aspects of data that we need to know to deal with machine learning. We discussed the different segregation of machine learning and the different machine learning algorithms. We also dealt with real-world platforms that are available on this sector.

Finally, we learned the hands-on aspects of machine learning, IDE installation, installation of packages, and setting up the environment for work. Finally, we took an example and worked on it from end to end.

In the next chapter, we will learn about time series analysis and ensemble modelling.