Software plagiarism detection: A graph-based approach
- Authors
- Chae, Dong-Kyu; Ha, Jiwoon; Kim, Sang-Wook; Kang, Boo Joong; Im, Eul Gyu
- Issue Date
- Oct-2013
- Publisher
- Association for Computing Machinary, Inc.
- Keywords
- Binary analysis; Graph; Similarity; Software plagiarism
- Citation
- International Conference on Information and Knowledge Management, Proceedings, pp.1577 - 1580
- Indexed
- SCOPUS
- Journal Title
- International Conference on Information and Knowledge Management, Proceedings
- Start Page
- 1577
- End Page
- 1580
- URI
- https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/161772
- DOI
- 10.1145/2505515.2507848
- ISSN
- 0000-0000
- Abstract
- As plagiarism of software increases rapidly, there are growing needs for software plagiarism detection systems. In this paper, we propose a software plagiarism detection system using an APIlabeled control flow graph (A-CFG) that abstracts the functionalities of a program. The A-CFG can reflect both the sequence and the frequency of APIs, while previous work rarely considers both of them together. To perform a scalable comparison of a pair of A-CFGs, we use random walk with restart (RWR) that computes an importance score for each node in a graph. By the RWR, we can generate a single score vector for an A-CFG and can also compare A-CFGs by comparing their score vectors. Extensive evaluations on a set of Windows applications demonstrate the effectiveness and the scalability of our proposed system compared with existing methods.
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