Malware Classification Method Using API Call Categorization


연구 분야: Safety



학회: ICONETSI '22: Proceedings of the 2022 International Conference on Engineering and Information Technology for Sustainable Industry


초록

The development of malware and computer security countermeasures is in a continuous arms race. Malware authors will adapt their malware according to the current state of events to maximize their chance of success. This increases the value of rapidly detecting the presence of malware within a system and identifying the type of malware. This research proposes a new method of classifying malware using API call categorization based on markov chain. The proposed methods have demonstrated a moderate accuracy of 87.19% with an f-1 score of 75.18%.


Author Profile
Andre Wijaya

Swiss German University Indonesia

Indonesia
Author Profile
Charles Lim

Swiss German University Indonesia

Indonesia
Author Profile
Yohanes Syailendra Kotualubun

Swiss German University Indonesia

Indonesia

📄 논문 정보

발행 연도 2022년
인용수 1
출판 국가 Indonesia
사이트 ACM
좋아요 수 0

연관 논문 목록 (272건)