AI-Based Smart Online Proctoring System for Real-Time Malpractice Detection in Remote Examinations

The rapid adoption of online education has introduced serious concerns regarding fairness and academic integrity in

remote examinations. This work presents a smart AI-enabled proctoring system that performs continuous monitoring of

candidates using video, audio, and behavioral signals. The proposed approach is based on a multi-modal fusion strategy that

combines outputs from different detection modules into a unified fraud assessment score. The system identifies suspicious

patterns such as impersonation, presence of additional individuals, usage of unauthorized devices, abnormal head movement,

and irregular audio activity. Experimental evaluation demonstrates an overall accuracy of 94% along with real-time processing

performance of 30 frames per second, making the system suitable for scalable deployment.