Towards automated verification of multi-party consensus protocols
This work addresses the need for automated verification in blockchain systems, specifically for enterprise applications using Hyperledger Fabric, though it appears incremental as it applies existing verification methods to this domain.
The paper tackles the problem of verifying blockchain multi-party consensus protocols with probabilistic properties, proposing a verification technique using statistical model checking and hypothesis testing that demonstrates experimental results to make models satisfy specifications.
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.