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MANIAC: A Man-Machine Collaborative System for Classifying Malware Author Groups
- Kim, Eujeanne;
- Park, Sung-Jun;
- Choi, Seokwoo;
- Chae, Dong-Kyu;
- Kim, Sang-Wook
Citations
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3Citations
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5초록
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 classification; malware authors; malware classification
- 제목
- MANIAC: A Man-Machine Collaborative System for Classifying Malware Author Groups
- 저자
- Kim, Eujeanne; Park, Sung-Jun; Choi, Seokwoo; Chae, Dong-Kyu; Kim, Sang-Wook
- 발행일
- 2021-11
- 유형
- Proceedings Paper
- 저널명
- CCS '21: PROCEEDINGS OF THE 2021 ACM SIGSAC CONFERENCE ON COMPUTER AND COMMUNICATIONS SECURITY
- 페이지
- 2441 ~ 2443