Same Same But Different: Preventing Refactoring Attacks on Software Plagiarism Detection

• URL: http://arxiv.org/abs/2510.25057v1
• Date: Wed, 29 Oct 2025 00:48:35 GMT
• Title: Same Same But Different: Preventing Refactoring Attacks on Software Plagiarism Detection
• Authors: Robin Maisch, Larissa Schmid, Timur Sağlam, Nils Niehues,
• Abstract summary: This paper presents a novel and framework that enhances state-of-the-art detectors by leveraging code property graphs and graph transformations.<n>Our comprehensive evaluation of real-world student submissions, obfuscated using both algorithmic and AI-based obfuscation attacks, demonstrates a significant improvement in detecting plagiarized code.
• Score: 1.876319405373752
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Plagiarism detection in programming education faces growing challenges due to increasingly sophisticated obfuscation techniques, particularly automated refactoring-based attacks. While code plagiarism detection systems used in education practice are resilient against basic obfuscation, they struggle against structural modifications that preserve program behavior, especially caused by refactoring-based obfuscation. This paper presents a novel and extensible framework that enhances state-of-the-art detectors by leveraging code property graphs and graph transformations to counteract refactoring-based obfuscation. Our comprehensive evaluation of real-world student submissions, obfuscated using both algorithmic and AI-based obfuscation attacks, demonstrates a significant improvement in detecting plagiarized code.

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