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Virus Detection Method based on Behavior Resource Tree
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  • Virus Detection Method based on Behavior Resource Tree
  • Virus Detection Method based on Behavior Resource Tree
저자명
Zou. Mengsong,Han. Lansheng,Liu. Ming,Liu. Qiwen
간행물명
Journal of information processing systems
권/호정보
2011년|7권 1호|pp.173-186 (14 pages)
발행정보
한국정보처리학회
파일정보
정기간행물|ENG|
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이 논문은 한국과학기술정보연구원과 논문 연계를 통해 무료로 제공되는 원문입니다.
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기타언어초록

Due to the disadvantages of signature-based computer virus detection techniques, behavior-based detection methods have developed rapidly in recent years. However, current popular behavior-based detection methods only take API call sequences as program behavior features and the difference between API calls in the detection is not taken into consideration. This paper divides virus behaviors into separate function modules by introducing DLLs into detection. APIs in different modules have different importance. DLLs and APIs are both considered program calling resources. Based on the calling relationships between DLLs and APIs, program calling resources can be pictured as a tree named program behavior resource tree. Important block structures are selected from the tree as program behavior features. Finally, a virus detection model based on behavior the resource tree is proposed and verified by experiment which provides a helpful reference to virus detection.