Interpreted and Confidential Execution of Process Choreographies on a Blockchain

Abstract

In our work, we refine the application of blockchain technology for managing inter-organizational business processes without a centralized authority, addressing the issue of data privacy inherent in public blockchains. Building on the proposal of Toldi and Kocsis, which involves recording encrypted instance data and reference hashes in smart contracts and aligning with business process models through zero-knowledge succinct arguments of knowledge (zk-SNARKs), we are able to improve several key metrics. Our approach introduces an efficient blockchain-based system tailored for business process modeling notation (BPMN) process choreographies. Unlike many other approaches in the field of blockchain-based process enactment, our system eliminates the need to deploy process-specific smart contracts. This alteration reduces the cost of instantiating new medium-sized process models by at least 88% compared to Toldi and Kocsis. Additionally, we achieve a greater than 99% reduction in the time required to generate conformance proofs. These enhancements result in a more cost-effective and streamlined approach for the private execution of choreographies on a blockchain.