Development of a Performance Evaluation Model on Similarity Measurement Method of Malware

악성코드 유사도 측정 기법의 성능 평가 모델 개발

  • 천성택 (공주대학교 융합과학과) ;
  • 김희석 (한국과학기술정보연구원 과학기술사이버안전센터) ;
  • 임광혁 (배재대학교 전자상거래학과) ;
  • 김규일 (한국과학기술정보연구원 과학기술사이버안전센터) ;
  • 서창호 (공주대학교 융합과학과)
  • Received : 2014.08.27
  • Accepted : 2014.09.11
  • Published : 2014.10.28


While there is a great demand for malware classification to reduce the time required in malware analysis and find a new type of malware, various similarity measurement methods of malware to classify a lot of malwares have been proposed. But, the existing methods to measure similarity just represented the classification results by them and have not carried out performance comparison with other methods. This is because an evaluation model to compare the performance of similarity measurement methods is non-existent. In this paper, we propose a new performance evaluation model on similarity measurement methods of malware by using two indicators: success rate and degree of confidence. In addition, we compare and evaluate the performance of existing similarity measurement methods by using these two indicators.


Malware Classification;Similarity Measurement Method;Static Analysis;Dynamic Analysis;Honeypot


Grant : 대용량 보안 이벤트 자동검증 고도화 기술연구

Supported by : 한국과학기술정보연구원


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