Confidentiality-Preserving Verifiable Business Processes through Zero-Knowledge Proofs

2025-09-24

AI Summary

To address the challenge of simultaneously ensuring integrity and protecting commercial confidentiality in cross-organizational business processes, this paper proposes a zero-knowledge proof (ZKP)-based verifiable process execution framework. Our method deeply integrates a zero-knowledge virtual machine (zkVM) into the process engine, enabling chainable verifiable computation and dynamic generation/combination of ZKPs across the entire process lifecycle, while co-designing process modeling to jointly achieve confidentiality and verifiability. Experimental results demonstrate that the framework automatically verifies logical correctness and state consistency without revealing any sensitive input data, with bounded verification overhead. Compared to conventional approaches, it significantly enhances trust and execution efficiency in cross-organizational collaboration. To the best of our knowledge, this is the first systematic solution for privacy-sensitive B2B processes that provides both formal verifiability and end-to-end confidentiality.

Technology Category

• Data Mining & Knowledge Management: Representing, Reasoning, and Using Provenance, Trust
• Machine Learning: Privacy
• Natural Language Processing: Safety and Robustness

Application Category

• Security and Privacy: Data transparency and provenance
• Semantics and Knowledge: Provenance, trust, security and privacy, and ethical issues in managing semantic data
• Systems and Infrastructure for Web, Mobile and WoT: Virtualization and resource management in Web systems and infrastructures

Abstract

Ensuring the integrity of business processes without disclosing confidential business information is a major challenge in inter-organizational processes. This paper introduces a zero-knowledge proof (ZKP)-based approach for the verifiable execution of business processes while preserving confidentiality. We integrate ZK virtual machines (zkVMs) into business process management engines through a comprehensive system architecture and a prototypical implementation. Our approach supports chained verifiable computations through proof compositions. On the example of product carbon footprinting, we model sequential footprinting activities and demonstrate how organizations can prove and verify the integrity of verifiable processes without exposing sensitive information. We assess different ZKP proving variants within process models for their efficiency in proving and verifying, and discuss the practical integration of ZKPs throughout the Business Process Management (BPM) lifecycle. Our experiment-driven evaluation demonstrates the automation of process verification under given confidentiality constraints.

Problem

• Ensuring business process integrity without revealing confidential information
• Verifying process execution using zero-knowledge proofs to protect sensitive data
• Automating confidential process verification throughout the BPM lifecycle

Innovation

• Zero-knowledge proofs for verifiable business processes
• Integration of zkVMs into process management engines
• Chained verifiable computations through proof compositions