Towards automated verification of multi-party consensus protocols

TL;DR

This paper presents a novel verification method for blockchain multi-party consensus protocols, specifically Hyperledger Fabric's endorsement policies, using statistical model checking and hypothesis testing to ensure probabilistic properties.

Contribution

It introduces a probabilistic verification approach for blockchain consensus protocols, enabling analysis of endorsement policies with weights and refusal probabilities.

Findings

Effective verification of endorsement policies demonstrated

Analysis of organizational weights and refusal probabilities

Experimental results show practical applicability

Abstract

Blockchain technology and related frameworks have recently received extensive attention. Blockchain systems use multi-party consensus protocols to reach agreements on transactions. Hyperledger Fabric framework exposes a multi-party consensus, based on endorsement policy protocol, to reach a consensus on a transaction. In this paper, we define a problem of verification of a blockchain multi-party consensus with probabilistic properties. Further, we propose a verification technique of endorsement policies using statistical model checking and hypothesis testing. We analyze several aspects of the policies, including the ability to assign weights to organizations and the refusal probabilities of organizations. We demonstrate on experiments the work of our verification technique and how one can use experimental results to make the model satisfiable the specification. One can use our technique to design enterprise applications with the Hyperledger Fabric framework.