Decentralized Consensus Algorithms with Byzantine Fault Tolerance using Differential Privacy

Abstract

This paper proposes a novel decentralized consensus algorithm designed to achieve Byzantine fault tolerance while simultaneously incorporating differential privacy mechanisms. The core idea is to leverage a blockchain-inspired architecture for transaction validation and agreement, enhanced with encrypted transactions and a randomized consensus protocol. Crucially, noise is injected into the consensus process to obscure individual contributions, thereby satisfying differential privacy constraints. The algorithm addresses the critical challenge of combining security and privacy in distributed systems, offering a robust solution for applications requiring both data integrity and user privacy protection. We formally define the algorithm, outlining the key components and their interactions, and analyze its properties regarding fault tolerance, privacy guarantees, and performance. The approach represents a significant step towards practical decentralized systems capable of handling malicious actors while respecting individual user data. The presented framework provides a foundation for future research and development in this increasingly important area.