poster

Software plagiarism detection: a graph-based approach

Authors:

Eul Gyu ImAuthors Info & Claims

CIKM '13: Proceedings of the 22nd ACM international conference on Information & Knowledge Management

Pages 1577 - 1580

https://doi.org/10.1145/2505515.2507848

Published: 27 October 2013 Publication History

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 API-labeled 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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Digital Library

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D. Chae, S. Kim, J. Ha, S. Lee, and G. Woo, "Software Plagiarism Detection via the Static API Call Frequency Birthmark," ACM SAC, pp. 1639--1643, 2013.

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Cited By

Paiva JLeal JFigueira Á(2024)Comparing semantic graph representations of source code: The case of automatic feedback on programming assignmentsComputer Science and Information Systems10.2298/CSIS230615004P21:1(117-142)Online publication date: 2024
https://doi.org/10.2298/CSIS230615004P
Song ZZhou YDong SZhang KZhang KFilkov VRay BZhou M(2024)TypeFSL: Type Prediction from Binaries via Inter-procedural Data-flow Analysis and Few-shot LearningProceedings of the 39th IEEE/ACM International Conference on Automated Software Engineering10.1145/3691620.3695502(1269-1281)Online publication date: 27-Oct-2024
https://dl.acm.org/doi/10.1145/3691620.3695502
Sağlam TBrödel MSchmid LHahner SRoychoudhury APaiva AAbreu RStorey M(2024)Detecting Automatic Software Plagiarism via Token Sequence NormalizationProceedings of the IEEE/ACM 46th International Conference on Software Engineering10.1145/3597503.3639192(1-13)Online publication date: 20-May-2024
https://dl.acm.org/doi/10.1145/3597503.3639192
Show More Cited By

Index Terms

Software plagiarism detection: a graph-based approach
1. Information systems
  1. Information systems applications
    1. Data mining

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cover image ACM Conferences

CIKM '13: Proceedings of the 22nd ACM international conference on Information & Knowledge Management

October 2013

2612 pages

ISBN:9781450322638

DOI:10.1145/2505515

General Chairs:
Qi He
LinkedIn, USA
,
Arun Iyengar
IBM T.J. Watson Research Center, USA
,
Program Chairs:
Wolfgang Nejdl
L3S Research Center, Germany
,
Jian Pei
Simon Fraser University, Canada
,
Rajeev Rastogi
Amazon, India

Copyright © 2013 ACM.

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Publication History

Published: 27 October 2013

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CIKM'13: 22nd ACM International Conference on Information and Knowledge Management

October 27 - November 1, 2013

California, San Francisco, USA

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CIKM '13 Paper Acceptance Rate 143 of 848 submissions, 17%;

Overall Acceptance Rate 1,861 of 8,427 submissions, 22%

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Cited By

Paiva JLeal JFigueira Á(2024)Comparing semantic graph representations of source code: The case of automatic feedback on programming assignmentsComputer Science and Information Systems10.2298/CSIS230615004P21:1(117-142)Online publication date: 2024
https://doi.org/10.2298/CSIS230615004P
Song ZZhou YDong SZhang KZhang KFilkov VRay BZhou M(2024)TypeFSL: Type Prediction from Binaries via Inter-procedural Data-flow Analysis and Few-shot LearningProceedings of the 39th IEEE/ACM International Conference on Automated Software Engineering10.1145/3691620.3695502(1269-1281)Online publication date: 27-Oct-2024
https://dl.acm.org/doi/10.1145/3691620.3695502
Sağlam TBrödel MSchmid LHahner SRoychoudhury APaiva AAbreu RStorey M(2024)Detecting Automatic Software Plagiarism via Token Sequence NormalizationProceedings of the IEEE/ACM 46th International Conference on Software Engineering10.1145/3597503.3639192(1-13)Online publication date: 20-May-2024
https://dl.acm.org/doi/10.1145/3597503.3639192
Folea RSlusanschi E(2024)On Plagiarism and Software PlagiarismAdvances in Computational Collective Intelligence10.1007/978-3-031-70259-4_24(314-326)Online publication date: 9-Sep-2024
https://doi.org/10.1007/978-3-031-70259-4_24
Filippov AStroeva J(2024)Search for Structurally Similar Projects of Software SystemsAdvances in Automation V10.1007/978-3-031-51127-1_2(15-26)Online publication date: 4-Jan-2024
https://doi.org/10.1007/978-3-031-51127-1_2
Hrkút PĎuračík MToth ŠMeško M(2023)Current Trends in the Search for Similarities in Source Codes with an Application in the Field of Plagiarism and Clone Detection2023 33rd Conference of Open Innovations Association (FRUCT)10.23919/FRUCT58615.2023.10143064(77-84)Online publication date: 24-May-2023
https://doi.org/10.23919/FRUCT58615.2023.10143064
Xu XXuan ZFeng SCheng SYe YShi QTao GYu LZhang ZZhang XChandra SBlincoe KTonella P(2023)PEM: Representing Binary Program Semantics for Similarity Analysis via a Probabilistic Execution ModelProceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering10.1145/3611643.3616301(401-412)Online publication date: 30-Nov-2023
https://dl.acm.org/doi/10.1145/3611643.3616301
Xu XFeng SYe YShen GSu ZCheng STao GShi QZhang ZZhang XJust RFraser G(2023)Improving Binary Code Similarity Transformer Models by Semantics-Driven Instruction DeemphasisProceedings of the 32nd ACM SIGSOFT International Symposium on Software Testing and Analysis10.1145/3597926.3598121(1106-1118)Online publication date: 12-Jul-2023
https://dl.acm.org/doi/10.1145/3597926.3598121
Bu SCho S(2023)Triplet-trained graph transformer with control flow graph for few-shot malware classificationInformation Sciences10.1016/j.ins.2023.119598649(119598)Online publication date: Nov-2023
https://doi.org/10.1016/j.ins.2023.119598
Nazir SKhan H(2023)An Overview on the Identification of Software Birthmarks for Software ProtectionProceedings of International Conference on Information Technology and Applications10.1007/978-981-19-9331-2_27(323-330)Online publication date: 19-May-2023
https://doi.org/10.1007/978-981-19-9331-2_27
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