The goal of this chapter is to introduce cybersecurity professionals to the basics of machine learning. We introduce the overall architecture for running machine learning modules and go through in great detail the different subtopics in the machine learning landscape.
There are many books on machine learning that deal with practical use cases, but very few address the cybersecurity and the different stages of the threat life cycle. This book is aimed at cybersecurity professionals who are looking to detect threats 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 as follows:
- Definitions of machine learning and use cases
- Delving into machine learning in the cybersecurity world
- Different types of machine learning systems
- Different data preparation techniques
- Machine learning architecture
- A more detailed look at statistical models and machine learning models
- Model tuning to ensure model performance and accuracy
- Machine learning tools
