Keystroke Analysis in Digital Test Security: AI Approaches for Copy-Typing Detection and Cheating Ring Identification

Chenhao Niu, Yong-Siang Shih, Manqian Liao, Ruidong Liu, Angel Ortmann Lee


Abstract
This project leverages AI-based analysis of keystroke and mouse data to detect copy-typing and identify cheating rings in the Duolingo English Test. By modeling behavioral biometrics, the approach provides actionable signals to proctors, enhancing digital test security for large-scale online assessment.
Anthology ID:
2025.aimecon-wip.13
Volume:
Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Works in Progress
Month:
October
Year:
2025
Address:
Wyndham Grand Pittsburgh, Downtown, Pittsburgh, Pennsylvania, United States
Editors:
Joshua Wilson, Christopher Ormerod, Magdalen Beiting Parrish
Venue:
AIME-Con
SIG:
Publisher:
National Council on Measurement in Education (NCME)
Note:
Pages:
107–116
Language:
URL:
https://aclanthology.org/2025.aimecon-wip.13/
DOI:
Bibkey:
Cite (ACL):
Chenhao Niu, Yong-Siang Shih, Manqian Liao, Ruidong Liu, and Angel Ortmann Lee. 2025. Keystroke Analysis in Digital Test Security: AI Approaches for Copy-Typing Detection and Cheating Ring Identification. In Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Works in Progress, pages 107–116, Wyndham Grand Pittsburgh, Downtown, Pittsburgh, Pennsylvania, United States. National Council on Measurement in Education (NCME).
Cite (Informal):
Keystroke Analysis in Digital Test Security: AI Approaches for Copy-Typing Detection and Cheating Ring Identification (Niu et al., AIME-Con 2025)
Copy Citation:
PDF:
https://aclanthology.org/2025.aimecon-wip.13.pdf