A Deep Approach to an Energy-Efficient Voting-Based Consensus Algorithm for Secure Financial Transactions

Blockchain consensus mechanisms like Proof-of-Work (PoW) and Proof-of-Stake (PoS) face critical challenges in energy efficiency and latency for financial transactions. In the study we devises VoteChain, a novel voting-based consensus algorithm enhanced by deep lightweight anomaly detection. We derive a rigorous energy-latency tradeoff model and integrate a Convolutional Neural Network (CNN) for real-time fraud detection. In the study we use opensource datasets and tested that VoteChain reduces energy consumption to 20.0 mWh/tx (98% lower than PoW) while achieving 65 Tps throughput and 1.2 ms latency, outperforming PoW, PoS, and PBFT. Whereas fault tolerance reaches 99.5% and validated via Byzantine attack simulations. In the study, we explored a scalable, eco-friendly solution for decentralized financial transactions.