AI Problems and Methods
In the previous chapters, you learned some basic definitions and taxonomies regarding artificial intelligence. This chapter will help you enhance this foundation and learn about concrete AI methods that are applied in cybersecurity. The knowledge from this chapter will help you get an idea of how different methods work and in what type of problems they are applicable. Furthermore, you will learn the advantages and disadvantages of applying these methods in particular conditions.
We’ll start by looking at the main categories of machine learning methods and describe example methods relevant to this book:
- Supervised learning methods
- Unsupervised learning methods
- Semi-supervised learning methods
- Anomaly detection
We’ll show some examples of various methods, including those from the supervised machine learning (random forest and neural networks), unsupervised learning (K-means, DBScan, and t-SNE) and semi-supervised learning...
