RAMC: runtime abstract memory context based plagiarism detection in binary code

  • Authors:

  • Yongsuk Choi;Yeongseong Park;Jongmoo Choi;Seong-je Cho;Hwansoo Han

  • Affiliations:

  • Dankook University, Yongin, Korea;Dankook University, Yongin, Korea;Dankook University, Yongin, Korea;Dankook University, Yongin, Korea;Sungkyunkwan University, Suwon, Korea

  • Venue:
  • Proceedings of the 7th International Conference on Ubiquitous Information Management and Communication
  • Year:
  • 2013

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Abstract

Analyzing software similarity has emerged as a key ingredient for various applications such as software maintenance, bug finding, malware clustering and copyright protection. In this paper, we propose a novel software similarity analysis tool for plagiarism detection. The tool, which we refer to it as RAMC (Runtime Abstract Memory Context based tool), has the following three characteristics. First, it is based on runtime semantic information, which makes it feasible to investigate similarity in binary codes, without source codes. Second, among runtime semantic information, it focuses on AMC (Abstract Memory Context) that can represent the intrinsic features of the analyzed code. Finally, it introduces two advanced techniques, namely region filtering and sequence alignment for AMC comparison. Real implementation based experiments have shown that RAMC can identify similarity appropriately between the original and plagiarized binaries.