MANIAC: A Man-Machine Collaborative System for Classifying Malware Author Groups

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초록

In this demo, we show MANIAC, a MAN-machIne collaborative system for malware Author Classification. It is developed to fight a number of author groups who have been generating lots of new malwares by sharing source code within a group and exploiting evasive schemes such as polymorphism and metamorphism. Notably, MANIAC allows users to intervene in the model's classification of malware authors with high uncertainty. It also provides effective interfaces and visualizations with users to achieve maximum classification accuracy with minimum human labor.

키워드

interactive classificationmalware authorsmalware classification
제목
MANIAC: A Man-Machine Collaborative System for Classifying Malware Author Groups
저자
Kim, EujeannePark, Sung-JunChoi, SeokwooChae, Dong-KyuKim, Sang-Wook
DOI
10.1145/3460120.3485355
발행일
2021-11
유형
Proceedings Paper
저널명
CCS '21: PROCEEDINGS OF THE 2021 ACM SIGSAC CONFERENCE ON COMPUTER AND COMMUNICATIONS SECURITY
페이지
2441 ~ 2443

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