연구 분야: Safety
학회: 2022 IEEE 6th Conference on Energy Internet and Energy System Integration (EI2)
The past decades witness the development of various Machine Learning (ML) models for malware classification. Semantic representation is a crucial basis for these classifiers. This paper aims to assess the effect of semantic representation methods on malware classifier performance. Two commonly-used semantic representation methods including N-gram and GloVe. We utilize diverse ML classifiers to conduct comparative experiments to analyze the capability of N-gram, GloVe and image-based methods for malware classification. We also analyze deeply the reason why the GloVe can produce negative effects on malware static analysis.
| 발행 연도 | 2022년 |
|---|---|
| 인용수 | 37 |
| 출판 국가 | Andorra, China |
| 사이트 | IEEE |
| 좋아요 수 | 0 |