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Human-in-the-Loop AI for Cheating Ring Detection

Yong-Siang Shih, Manqian Liao, Ruidong Liu, Mirza Basim Baig

TL;DR

A human-in-the-loop AI cheating ring detection system designed to detect and deter professional cheating services aiding malicious test takers in passing exams, forming so-called cheating rings is introduced.

Abstract

Online exams have become popular in recent years due to their accessibility. However, some concerns have been raised about the security of the online exams, particularly in the context of professional cheating services aiding malicious test takers in passing exams, forming so-called "cheating rings". In this paper, we introduce a human-in-the-loop AI cheating ring detection system designed to detect and deter these cheating rings. We outline the underlying logic of this human-in-the-loop AI system, exploring its design principles tailored to achieve its objectives of detecting cheaters. Moreover, we illustrate the methodologies used to evaluate its performance and fairness, aiming to mitigate the unintended risks associated with the AI system. The design and development of the system adhere to Responsible AI (RAI) standards, ensuring that ethical considerations are integrated throughout the entire development process.

Human-in-the-Loop AI for Cheating Ring Detection

TL;DR

A human-in-the-loop AI cheating ring detection system designed to detect and deter professional cheating services aiding malicious test takers in passing exams, forming so-called cheating rings is introduced.

Abstract

Online exams have become popular in recent years due to their accessibility. However, some concerns have been raised about the security of the online exams, particularly in the context of professional cheating services aiding malicious test takers in passing exams, forming so-called "cheating rings". In this paper, we introduce a human-in-the-loop AI cheating ring detection system designed to detect and deter these cheating rings. We outline the underlying logic of this human-in-the-loop AI system, exploring its design principles tailored to achieve its objectives of detecting cheaters. Moreover, we illustrate the methodologies used to evaluate its performance and fairness, aiming to mitigate the unintended risks associated with the AI system. The design and development of the system adhere to Responsible AI (RAI) standards, ensuring that ethical considerations are integrated throughout the entire development process.
Paper Structure (6 sections, 1 figure, 2 tables)

This paper contains 6 sections, 1 figure, 2 tables.

Table of Contents

  1. Introduction
  2. System Overview
  3. Keystroke and Mouse Movement Pattern Analysis
  4. Proctoring Interface
  5. System Evaluation
  6. Discussion

Figures (1)

  • Figure 1: When proctoring the current test session, our cheating ring detection system may detect related test sessions to be shown to the proctors. The proctors can further investigate each test session by clicking on the test sessions.