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Mitigating Automated Obfuscation Attacks on Software Plagiarism Detection Systems

Plagiarism is a prevalent challenge in computer science education, and educators rely on detection systems to address it at scale. However, these systems remain vulnerable to obfuscation attacks that alter the structure of a program while preserving its behavior. Recent advancements in artificial in...

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Hovedforfatter: Saglam, Timur
Format: Online
Sprog:engelsk
Udgivet: KIT Scientific Publishing 2026
Fag:
Computer Science Education
Informatikausbildung
Obfuscation Attacks
Plagiarism Detection
Plagiatserkennung
Programmierausbildung
Programming Education
Quellcode-Plagiate
Source Code Plagiarism
Verschleierungsangriffe
thema EDItEUR::U Computing and Information Technology::UY Computer science
Online adgang:ONIX_20260621T103021_9783731514558_13
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Summary:Plagiarism is a prevalent challenge in computer science education, and educators rely on detection systems to address it at scale. However, these systems remain vulnerable to obfuscation attacks that alter the structure of a program while preserving its behavior. Recent advancements in artificial intelligence have exacerbated this problem. To address these challenges, this dissertation introduces defense mechanisms against automated obfuscation, enhancing the resilience of detection systems.

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