Cluster Analysis of Malware Family Relationships

2021/03/07 by Samanvitha Basole, Basole, Samanvitha, Mark Stamp +1 · 1 citation
Computer Science · #Advanced Malware Detection Techniques #Cryptography and Security (cs.CR) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Network Security and Intrusion Detection

paper · pdf · doi:10.48550/arxiv.2103.05761

openalex publication_date 2021/03/07 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

In this paper, we use K-means clustering to analyze various relationships between malware samples. We consider a dataset comprising~20 malware families with~1000 samples per family. These families can be categorized into seven different types of malware. We perform clustering based on pairs of families and use the results to determine relationships between families. We perform a similar cluster analysis based on malware type. Our results indicate that K-means clustering can be a powerful tool for data exploration of malware family relationships.

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