This study presents a comprehensive security system designed for electronic examinations (e exams) that utilizes Internet of Things (IoT) and fog computing technologies. As educational institutions increasingly transition to digital assessment methods, the need for robust security measures to safeguard exam integrity becomes critical. Our proposed system integrates IoT devices to monitor exam environments in real time, capturing candidate behavior and environmental conditions. By leveraging fog computing, data is processed at the network edge, ensuring low latency and facilitating immediate anomaly detection. The implementation of machine learning algorithms allows for the identification of suspicious activities, such as unauthorized device usage or cheating behaviors, with alerts sent to exam proctors in real time. This approach not only enhances the security of e-exams but also provides a scalable and efficient solution for educational institutions. Through extensive simulations and real-world testing, our research demonstrates the effectiveness of this system in maintaining exam integrity, contributing to the evolving landscape of secure digital assessments.