Mike Grace talks to Mike Joy. Interview by Mike Grace

Joy, Michael

doi:10.1038/sj.bdj.4809582

Cited by 1 publication

(1 citation statement)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As far as the authors are aware, there have not been any substantial changes to any of these tools since this disclosure. In response to the disclosure, the authors had conversations with both Alex Aiken (of Moss) and Mike Joy (of Sherlock) regarding previous attacks against each of the respective tools and discussion of Mossad [Aiken 2018;Joy 2020]. The authors did not receive a response from the authors of JPlag.…”

Section: Ethical Considerationsmentioning

confidence: 99%

Mossad: Defeating Software Plagiarism Detection

Devore-McDonald¹,

Berger²

2020

Preprint

View full text Add to dashboard Cite

Automatic software plagiarism detection tools are widely used in educational settings to ensure that submitted work was not copied. These tools have grown in use together with the rise in enrollments in computer science programs and the widespread availability of code on-line. Educators rely on the robustness of plagiarism detection tools; the working assumption is that the effort required to evade detection is as high as that required to actually do the assigned work.This paper shows this is not the case. It presents an entirely automatic program transformation approach, Mossad, that defeats popular software plagiarism detection tools. Mossad comprises a framework that couples techniques inspired by genetic programming with domain-specific knowledge to effectively undermine plagiarism detectors. Mossad is effective at defeating four plagiarism detectors, including Moss [Schleimer et al. 2003] and JPlag [Prechelt et al. 2002]. Mossad is both fast and effective: it can, in minutes, generate modified versions of programs that are likely to escape detection. More insidiously, because of its nondeterministic approach, Mossad can, from a single program, generate dozens of variants, which are classified as no more suspicious than legitimate assignments. A detailed study of Mossad across a corpus of real student assignments demonstrates its efficacy at evading detection. A user study shows that graduate student assistants consistently rate Mossad-generated code as just as readable as authentic student code. This work motivates the need for both research on more robust plagiarism detection tools and greater integration of naturally plagiarism-resistant methodologies like code review into computer science education.CCS Concepts: • Software and its engineering → Genetic programming; Collaboration in software development; • Social and professional topics → Computer science education.

show abstract

Section: Ethical Considerationsmentioning

confidence: 99%