QUANTUM RESISTANT HOMOMORPHIC AND ZERO-KNOWLEDGE FEDERATED ELECTORAL FRAMEWORK FOR CONFIDENTIAL, AUTHENTIC, AND IMMUTABLE INTELLIGENT EVOTING SYSTEMS

Abstract

Secure electronic voting systems are being implemented as an effective method of preventing potential manipulation or disruption of democratic processes through means such as hacking, voter impersonation/identity theft, voter coercion, or large scale cyber attacks on distributed elections. However, existing blockchain based election systems continue to face many challenges including; quantum vulnerabilities within their underlying encryption protocols, scalability of consensus mechanisms to support larger numbers of voters, extended timeframes required to compute encrypted tallies, inability to detect fraudulent activity related to the context of specific votes cast, and lack of predictive models that can identify organized attack vectors during an election. In order to address each of these issues with respect to developing secure electronic voting systems using blockchain technology, this paper will outline a comprehensive cryptography framework for conducting elections. This framework will include four distinct components: the Quantum Lattice Trust Chain Ballot Validation Framework (QLTBBV); the Neuro Adaptive Homomorphic Consensus Voting Network (NAHCVN); the Bio Hash DAG Electoral Integrity Optimization Model (BDIEIM); the Zero Knowledge Swarm Consensus Electoral Framework (ZKSCF); and the Causal AI Federated Immutable Election Twin System (CAF-IETS). Each component of the QLTBBV framework provides a unique capability to provide secure, authenticated, transparent, and predictable voting systems by utilizing post-quantum lattice encryption, homomorphic encrypted tally calculations, bio-metric DAG propagation methods for ensuring election integrity, swarm based zero knowledge consensus algorithms, and causal federated digital twin methods to ensure all aspects of the voting process remain confidential while providing immutable records of every aspect of the voting process. Results from experimental testing showed 99.4% accuracy in verifying the authenticity of each vote, 99.1% reliability in computing encrypted tallies, 98.4% precision in detecting fraudulent activities associated with individual votes, and statistically significant improvements in reducing latency requirements for achieving consensus and reducing the likelihood of unauthorized tampering with any portion of the electronic voting systems.