Master of Science (MS)
Fabio Di Troia
In this research, we apply clustering techniques to the malware detection problem. Our goal is to classify malware as part of a fully automated detection strategy. We compute clusters using the well-known 𝐾-means and EM clustering algorithms, with scores obtained from Hidden Markov Models (HMM). The previous work in this area consists of using HMM and 𝐾-means clustering technique to achieve the same. The current effort aims to extend it to use EM clustering technique for detection and also compare this technique with the 𝐾-means clustering.
Pai, Swathi, "A Comparison of Clustering Techniques for Malware Analysis" (2015). Master's Projects. 404.