Chapter 1. Basics of Machine Learning in Cyber Security

The goal of this chapter is to introduce Cyber Security professionals to the basics of Machine Learning. We introduce to the readers the overall architecture for running Machine Learning modules and go through in great details the different subtopics in the machine learning landscape.  

The are many books of machine learning that are dealing with practical use-cases but very few address the cyber security and the different stages of the threat life cycle. This book is aimed for cyber security professionals who are looking forward to detect threat by applying machine learning and predictive analytics.

In this chapter we go through the basics of machine learning. The primary areas that we cover are:

•  Definitions of Machine Learning and use-cases
• Delving with machine learning the cyber security world
• Different Types of Machine  Learning Systems
• Different Data Preparation Techniques
• Machine Learning Architecture 
• A deeper dive to  statistical models and Machine Learning Models 
• Model Tuning to ensure model performance and accuracy
• Machine Learning Tools