Scholarlink

<p>Academic integrity aims to ensure that students’ achievements are the result of their own efforts and knowledge. However, academic dishonesty continues to evolve, becoming increasingly difficult to detect and mitigate—especially with the rise of sophisticated, AI-driven tools. The lack of a universal knowledge base and standardized guidelines for addressing emerging forms of misconduct further complicates enforcement, leaving educators with limited resources to effectively identify and respond to violations. This research addresses these challenges by proposing CheatGuard, a centralized online anti-cheating platform with incident reporting capabilities. Inspired by MITRE’s ATT&amp;CK framework used in cybersecurity, CheatGuard catalogs a wide range of cheating techniques reported by institutions—from plagiarism to unauthorized collaboration during exams. For each assessment category, it also provides corresponding detection and prevention methods. CheatGuard’s knowledge base is continuously updated using an AI agent that gathers data from online sources. Tactics, techniques, and procedures related to academic dishonesty are structured similarly to those in MITRE ATT&amp;CK, helping institutions systematically select appropriate countermeasures. This paper presents the conceptual architecture of CheatGuard, explains how it can be accessed and used by educators, and explores its potential to combat academic misconduct in the age of Artificial Intelligence.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

CheatGuard: A cybersecurity inspired anti-cheating platform for higher education

  • 期刊论文

  • 发表日期：

    2025年8月1日

查看全文
  • Imran Taj,
  • Sifan Waktole Dadi,
  • Ahmed Samer Wazan,
  • Romain Laborde,
  • Abdulhadi Shoufan

摘要

Academic integrity aims to ensure that students’ achievements are the result of their own efforts and knowledge. However, academic dishonesty continues to evolve, becoming increasingly difficult to detect and mitigate—especially with the rise of sophisticated, AI-driven tools. The lack of a universal knowledge base and standardized guidelines for addressing emerging forms of misconduct further complicates enforcement, leaving educators with limited resources to effectively identify and respond to violations. This research addresses these challenges by proposing CheatGuard, a centralized online anti-cheating platform with incident reporting capabilities. Inspired by MITRE’s ATT&CK framework used in cybersecurity, CheatGuard catalogs a wide range of cheating techniques reported by institutions—from plagiarism to unauthorized collaboration during exams. For each assessment category, it also provides corresponding detection and prevention methods. CheatGuard’s knowledge base is continuously updated using an AI agent that gathers data from online sources. Tactics, techniques, and procedures related to academic dishonesty are structured similarly to those in MITRE ATT&CK, helping institutions systematically select appropriate countermeasures. This paper presents the conceptual architecture of CheatGuard, explains how it can be accessed and used by educators, and explores its potential to combat academic misconduct in the age of Artificial Intelligence.