{"title":"Zero-Knowledge Process Verification: A Comprehensive Framework for a Distributed Healthcare System.","authors":"Sathya Krishnasamy","doi":"10.30953/bhty.v9.430","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>This article introduces the ZK-PRET Business Process Prover framework that integrates Object Management Group (OMG) business process standards with zero-knowledge cryptographic verification to enable privacy-preserving healthcare process compliance across distributed systems.</p><p><strong>Methods: </strong>We developed a multilayer architecture combining formal business process modeling, zero-knowledge proof generation, and regulatory compliance verification. The framework extends established OMG standards with cryptographic verification capabilities to achieve verifiable compliance, privacy preservation, and regulatory accountability. Implementation testing were conducted in synthetic data environments designed to represent real-world healthcare scenarios.<sup>1</sup> These environments enable comprehensive modeling and testing of multi-entity process orchestration patterns while maintaining privacy protections essential for healthcare research and development. All scenarios, clinical examples, and process expressions presented in this article utilize synthetic data to ensure no real patient data, clinical records, or identifiable health information were used.</p><p><strong>Results: </strong>The ZK-PRET Business Process Prover framework demonstrates practical applicability across many healthcare domains, including treatment planning, telemedicine coordination, healthcare administration, consumer health services, multientity clinical trials, and supply chain management. Implementation results demonstrate cryptographic verification capabilities that enable mathematical prevention of regulatory violations rather than post hoc detection. The results demonstrate configurable privacy preservation through zero-knowledge verification and consistent proof sizes suitable for modeling complex orchestrations, while leveraging already widely used Web 2 process models suitable for multiple runtime deployment topologies.</p><p><strong>Conclusions: </strong>Zero-knowledge healthcare process verification represents a foundational technology for regulatory compliance in distributed healthcare systems. While agentic AI systems present important opportunities for automation, the underlying requirement for verifiable process compliance through cryptographic means brings broader challenges. ZK-PRET Business Process Prover addresses these challenges in healthcare transformative flows, enabling safer deployment of autonomous systems while maintaining regulatory standards.</p>","PeriodicalId":72422,"journal":{"name":"Blockchain in healthcare today","volume":"9 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2026-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13186148/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Blockchain in healthcare today","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.30953/bhty.v9.430","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2026/1/1 0:00:00","PubModel":"eCollection","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Objective: This article introduces the ZK-PRET Business Process Prover framework that integrates Object Management Group (OMG) business process standards with zero-knowledge cryptographic verification to enable privacy-preserving healthcare process compliance across distributed systems.
Methods: We developed a multilayer architecture combining formal business process modeling, zero-knowledge proof generation, and regulatory compliance verification. The framework extends established OMG standards with cryptographic verification capabilities to achieve verifiable compliance, privacy preservation, and regulatory accountability. Implementation testing were conducted in synthetic data environments designed to represent real-world healthcare scenarios.1 These environments enable comprehensive modeling and testing of multi-entity process orchestration patterns while maintaining privacy protections essential for healthcare research and development. All scenarios, clinical examples, and process expressions presented in this article utilize synthetic data to ensure no real patient data, clinical records, or identifiable health information were used.
Results: The ZK-PRET Business Process Prover framework demonstrates practical applicability across many healthcare domains, including treatment planning, telemedicine coordination, healthcare administration, consumer health services, multientity clinical trials, and supply chain management. Implementation results demonstrate cryptographic verification capabilities that enable mathematical prevention of regulatory violations rather than post hoc detection. The results demonstrate configurable privacy preservation through zero-knowledge verification and consistent proof sizes suitable for modeling complex orchestrations, while leveraging already widely used Web 2 process models suitable for multiple runtime deployment topologies.
Conclusions: Zero-knowledge healthcare process verification represents a foundational technology for regulatory compliance in distributed healthcare systems. While agentic AI systems present important opportunities for automation, the underlying requirement for verifiable process compliance through cryptographic means brings broader challenges. ZK-PRET Business Process Prover addresses these challenges in healthcare transformative flows, enabling safer deployment of autonomous systems while maintaining regulatory standards.
目的:本文介绍了ZK-PRET业务流程证明程序框架,该框架将对象管理组(OMG)业务流程标准与零知识加密验证集成在一起,以实现跨分布式系统的隐私保护医疗流程合规性。方法:我们开发了一个结合正式业务流程建模、零知识证明生成和法规遵从性验证的多层体系结构。该框架通过加密验证功能扩展了已建立的OMG标准,以实现可验证的遵从性、隐私保护和监管责任。在旨在表示真实医疗保健场景的合成数据环境中进行了实现测试1这些环境支持对多实体流程编排模式进行全面建模和测试,同时维护医疗保健研究和开发所必需的隐私保护。本文中提供的所有场景、临床示例和流程表达式都使用合成数据,以确保不使用真实的患者数据、临床记录或可识别的健康信息。结果:ZK-PRET Business Process provider框架展示了在许多医疗保健领域的实际适用性,包括治疗计划、远程医疗协调、医疗保健管理、消费者健康服务、多实体临床试验和供应链管理。实现结果演示了加密验证功能,该功能支持对违反法规的数学预防,而不是事后检测。结果表明,通过零知识验证和一致的证明大小,可以实现可配置的隐私保护,适合对复杂编排进行建模,同时利用已经广泛使用的、适合多个运行时部署拓扑的Web 2流程模型。结论:零知识医疗保健流程验证代表了分布式医疗保健系统中法规遵从性的基础技术。虽然人工智能系统为自动化提供了重要的机会,但通过加密手段对可验证过程合规性的潜在需求带来了更广泛的挑战。ZK-PRET Business Process Prover解决了医疗保健变革流中的这些挑战,支持在保持监管标准的同时更安全地部署自主系统。