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
1
Basics of Machine Learning in Cybersecurity
5
Using Data Science to Catch Email Fraud and Spam

Modeling

This is a simple model that stocks in historical data features (the ones listed in the Data parsing section) that are associated with Windows logs. When a new feature parameter comes in, we see whether this is a new one by comparing to the historical data. Historical data could include AD logs with res to the features from over a year ago. The AD event that we will use for this purpose is 4672.

For the purposes of a use case, we will only choose the privilege feature. A list of privileges could be as follows:

  • SeSecurityPrivilege
  • SeTakeOwnershipPrivilege
  • SeLoadDriverPrivilege
  • SeBackupPrivilege
  • SeRestorePrivilege
  • SeDebugPrivilege
  • SeSystemEnvironmentPrivilege
  • SeImpersonatePrivilege

We store in the historical database all privileges that the user account had in the past year, such as the write privilege and the read privilege. When a new privilege is seen to be invoked...