CRYPTOPROCTOR: BLOCKCHAIN BASED SECURED ONLINE PROCTORING SYSTEM

Abstract

The rapid growth of online education and remote examinations has created a critical need for secure, transparent, and reliable online proctoring systems. Traditional proctoring solutions often rely on centralized architectures, making them vulnerable to data tampering, identity fraud, and privacy breaches. To address these challenges, this project proposes Cryptoproctor, a blockchain-based secured online proctoring system designed to ensure integrity, transparency, and trust in digital examinations. The proposed system integrates blockchain technology with artificial intelligence (AI) to provide a robust and tamper-proof examination environment. Blockchain is used to securely store exam records, student credentials, and activity logs in a decentralized ledger, ensuring immutability and transparency. Smart contracts automate processes such as exam registration, authentication, and result verification, eliminating the need for intermediaries. AI-based proctoring techniques, including facial recognition, eye movement tracking, and behavior analysis, are employed to monitor students in real time and detect suspicious activities such as impersonation, cheating, or unauthorized assistance. Additionally, the system ensures data privacy by encrypting sensitive information and storing only hash values on the blockchain. The integration of cloud computing enables scalability and real-time monitoring, while maintaining system performance. The proposed model is evaluated using metrics such as accuracy, detection rate, latency, and security analysis. Results indicate that CRYPTOPROCTOR provides enhanced security, reduced fraud, and improved trust compared to traditional proctoring systems. Overall, the system offers a scalable and intelligent solution for secure online examinations, supporting the growing demand for reliable digital education platforms.