Blockchain-based University Election System With Biometric Authentication And AI-driven Anomaly Detection

Uncategorized

Authors: Mr. M. Santhanaraj, S.Dharshini, R.Pooja, B.Devaki

Abstract: This project presents a Blockchain-based University Election System enhanced with biometric authentication and AI-driven anomaly detection to address the challenges of security, transparency, and reliability in student elections. The proposed system verifies voter identity through fingerprint and facial recognition, ensuring that only eligible students participate and eliminating risks of impersonation, duplicate, or proxy voting. Each vote is encrypted and immutably recorded on the blockchain ledger, preventing tampering, deletion, or manipulation while creating a transparent and verifiable audit trail. Smart contracts govern the election process by automating voter eligibility checks, enforcing the one-student-one-vote policy, scheduling the election, and instantly counting and publishing results without human intervention. The integration of AI adds another layer of protection by continuously analyzing voting behaviors, biometric data, and transaction patterns to detect anomalies, suspicious trends, or fraudulent activities in real time. This holistic approach reduces manual errors, enhances accountability, and builds student confidence in the election process through verifiable and tamper-proof outcomes. Additionally, the system is designed to be user-friendly, scalable, and cost-effective, making it adaptable not only for universities but also for larger institutions and government-level elections in the future. By combining blockchain, biometrics, and AI, this project demonstrates a secure, intelligent, and modern framework for conducting elections with integrity and efficiency

× How can I help you?