Block Chain-Enabled Secure E-Voting Framework with Facial Recognition for Voter Authentication

Democratic elections rely on trust, transparency, and tamper-resistance -- qualities that conventional and early electronic voting systems have consistently failed to guarantee. This paper presents a Blockchain-Enabled Secure E-Voting Framework with Facial Recognition for Voter Authentication, designed to address persistent vulnerabilities in existing electoral systems. The proposed system integrates a permissioned blockchain ledger with deep-learning-based facial biometric verification to ensure decentralized, immutable vote storage and strong identity assurance. A multi-layer security architecture  combines  homomorphic  encryption, zero-knowledge proofs, and digital signatures to preserve voter anonymity  while  enabling  end-to-end  verifiability. Anti-spoofing and liveness detection mechanisms prevent impersonation via photographs, video replays, or deepfake-generated imagery. Smart contracts automate vote counting and result publication, eliminating human involvement in the tallying process. Experimental evaluation demonstrates a facial recognition authentication accuracy of 97.3% and an end-to-end voting transaction latency under 500 milliseconds, with blockchain confirmation averaging 2.4 seconds. The framework is scalable to national-scale elections and applicable to governmental, corporate, and institutional governance contexts.

blockchain; e-voting; facial recognition; homomorphic encryption; zero-knowledge proof; smart contracts; biometric authentication; electoral integrity

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