Decentralized Verification of Blockchain Transactions using Distributed Bayesian Networks

Abstract

This paper proposes a novel decentralized blockchain verification system utilizing distributed Bayesian Networks (BNs). Traditional blockchain verification relies heavily on cryptographic proofs, which can be computationally intensive and susceptible to specialized attacks. Our approach offers a probabilistic and decentralized alternative. Each node maintains a Bayesian Network representing the blockchain's transaction graph, continuously updated with observed transactions. Consensus is achieved through iterative Bayesian inference and probabilistic agreement on the validity of new transactions. This system mitigates single points of failure, enhances security through probabilistic reasoning, and provides a more scalable verification process compared to traditional methods. The core claim is that a decentralized blockchain verification system can be built by leveraging distributed Bayesian Networks to model and verify transaction dependencies. The core mechanism involves continuous BN updates and consensus through iterative inference. This paper outlines the system architecture, the probabilistic inference process, and discusses potential applications and future research directions.