Published Paper Details:

The modernization of democratic elections through digital technologies offers vast opportunities but also introduces complex challenges. Traditional electronic voting (e-voting) mechanisms often suffer from vulnerabilities such as centralized data control, opacity in verification processes, and high susceptibility to manipulation or cyberattacks. To address these limitations, this study presents a hybrid framework integrating blockchain and artificial intelligence (AI) to achieve enhanced security, transparency, and scalability in e-voting. The blockchain layer ensures immutability and distributed trust through consensus-based verification, while the AI layer provides adaptive intelligence for real-time fraud detection, biometric voter authentication, and anomaly analysis. The designed framework integrates several essential modules for voter registration, biometric verification, vote casting, AI-driven fraud monitoring, blockchain anchoring, and audit visualization. Experimental simulations with over one million synthetic votes demonstrate fraud detection accuracy of 98.5%, biometric verification accuracy of 99.1%, and an average vote confirmation latency of 1.7 seconds, confirming the framework's feasibility for secure, large-scale elections. The results highlight that the synergy between blockchain's decentralization and AI's adaptivity can form the foundation for a next-generation digital democracy.