Publication Date
Spring 2021
Degree Type
Master's Project
Degree Name
Master of Science in Computer Science (MSCS)
Department
Computer Science
First Advisor
Mark Stamp
Second Advisor
William Andreopoulos
Third Advisor
Fabio Di Troia
Abstract
Automated techniques to classify malware samples into their respective families are critical in cybersecurity. Previously research applied ��-means clustering to scores generated by hidden Markov models (HMM) as a means of dealing with the malware classification problem. In this research, we follow a somewhat similar approach, but instead of using HMMs to generate scores, we directly cluster the HMMs themselves. We obtain good results on a challenging malware dataset.
Recommended Citation
Singh, Shamli, "Hidden Markov Model-based Clustering for Malware Classification" (2021). Master's Projects. 1008.
DOI: https://doi.org/10.31979/etd.8pte-6mqn
https://scholarworks.sjsu.edu/etd_projects/1008
