2 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.CR2022
Multifamily Malware Models
Samanvitha Basole, Fabio Di Troia, Mark Stamp
When training a machine learning model, there is likely to be a tradeoff between accuracy and the diversity of the dataset. Previous research has shown that if we train a model to…
cs.CR2021
Cluster Analysis of Malware Family Relationships
Samanvitha Basole, Mark Stamp
In this paper, we use -means clustering to analyze various relationships between malware samples. We consider a dataset comprising~20 malware families with~1000 samples per fami…
cs.CR2021★ 2 cited
Malware Classification with GMM-HMM Models
Jing Zhao, Samanvitha Basole, Mark Stamp
Discrete hidden Markov models (HMM) are often applied to malware detection and classification problems. However, the continuous analog of discrete HMMs, that is, Gaussian mixture m…