A Multi-Layered AI-Driven E-Proctoring System Using Wearable EEG and Secure IoT Integration for Cheating Prevention and Cybersecurity in Online Exams

With the proliferation of remote education and online assessments, maintaining academic integrity while ensuring cybersecurity has become a critical challenge. This paper proposes a comprehensive and intelligent e-proctoring system that integrates Artificial Intelligence (AI), wearable EEG technology, and secure Internet of Things (IoT) components within the Moodle learning management environment. The system combines multiple security and proctoring techniques: webcam-based facial and environmental monitoring, EEG signal analysis via a Muse2 headband for real-time stress and identity detection, and a restricted examination environment enforced by the Safe Exam Browser (SEB). To ensure robust security, a layered defense model is employed, incorporating multi-factor biometric authentication, IPSec-based encryption, VPN tunneling, and entity verification through challenge-response protocols. Experimental evaluations validate the system's effectiveness in preventing and detecting cheating, while performance analyses confirm minimal network impact even under VPN-enforced encryption. The proposed solution demonstrates a scalable, secure, and intelligent approach to safeguarding academic integrity in digital education.