Engineering Commons^™

Malicious Game Client Detection Using Feature Extraction And Machine Learning, Spencer J. Austad

Theses and Dissertations

Minecraft, the world's best-selling video game, boasts a vast and vibrant community of users who actively develop third-party software for the game. However, it has also garnered notoriety as one of the most malware-infested gaming environments. This poses a unique challenge because Minecraft software has many community-specific nuances that make traditional malware analysis less effective. These differences include unique file types, differing code formats, and lack of standardization in user-generated content analysis. This research looks at Minecraft clients in the two most common formats: Portable Executable and Java Archive file formats. Feature correlation matrices showed that malware features are too …