This project contains the notebooks developed as part of my Master’s thesis: Clustering Windows Malware using Static Features and Concept Drift Detection. (https://amslaurea.unibo.it/id/eprint/34458/)
The notebooks cover the entire clustering process, from preprocessing to the application of hierarchical algorithms.
Various dimensionality reduction algorithms and clustering techniques were evaluated, with the best configuration selected based on clustering quality scores (both unsupervised and supervised).
The code also includes experiments conducted for the chapter on explainable AI (XAI) for cluster analysis.
- Luca Fabri