JPlag

While software plagiarism detectors have been used for decades, the assumption that evading detection requires programming proficiency is challenged by the emergence of automated plagiarism generators. These generators enable effortless obfuscation attacks, exploiting vulnerabilities in existing detectors by inserting statements to disrupt the matching. We present a language-independent defense mechanism that leverages program dependence graphs, rendering such attacks infeasible. We evaluate our approach with multiple real-world datasets and show that it defeats plagiarism generators by offering resilience against automated obfuscation while maintaining a low rate of false positives.

Publication Details

Journal
Gesellschaft für Informatik (GI)
Published
2025-01-01
DOI
https://doi.org/10.18420/se2025-30
Primary Topic
Advanced Malware Detection Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

JPlag

Gesellschaft für Informatik (GI)
Advanced Malware Detection Techniques
article

JPlag

article en

Abstract

While software plagiarism detectors have been used for decades, the assumption that evading detection requires programming proficiency is challenged by the emergence of automated plagiarism generators. These generators enable effortless obfuscation attacks, exploiting vulnerabilities in existing detectors by inserting statements to disrupt the matching. We present a language-independent defense mechanism that leverages program dependence graphs, rendering such attacks infeasible. We evaluate our approach with multiple real-world datasets and show that it defeats plagiarism generators by offering resilience against automated obfuscation while maintaining a low rate of false positives.

Gesellschaft für Informatik (GI)
Openalex Percentile: Top 50%
Advanced Malware Detection Techniques
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JPlag · Gesellschaft für Informatik (GI) (2025) | TGRS Research Map | TGRS