ZK-DPPS: A Zero-Knowledge Decentralised Data Sharing and Processing Middleware
Amir Jabbari, Gowri Ramachandran, Sidra Malik, Raja Jurdak

TL;DR
ZK-DPPS introduces a privacy-preserving framework for decentralized data sharing in supply chains, combining FHE and SMPC to avoid traditional ZKPs, enhancing efficiency and flexibility in IoT-driven environments.
Contribution
It presents a novel zero-knowledge communication system that replaces traditional ZKPs with FHE and SMPC, improving privacy and efficiency in decentralized supply chain data sharing.
Findings
Successfully demonstrates privacy preservation in supply chain simulation
Reduces computational overhead compared to ZKP-based methods
Ensures data confidentiality during processing and sharing
Abstract
In the current digital landscape, supply chains have transformed into complex networks driven by the Internet of Things (IoT), necessitating enhanced data sharing and processing capabilities to ensure traceability and transparency. Leveraging Blockchain technology in IoT applications advances reliability and transparency in near-real-time insight extraction processes. However, it raises significant concerns regarding data privacy. Existing privacy-preserving approaches often rely on Smart Contracts for automation and Zero Knowledge Proofs (ZKP) for privacy. However, apart from being inflexible in adopting system changes while effectively protecting data confidentiality, these approaches introduce significant computational expenses and overheads that make them impractical for dynamic supply chain environments. To address these challenges, we propose ZK-DPPS, a framework that ensures…
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Taxonomy
TopicsDistributed and Parallel Computing Systems · Distributed systems and fault tolerance · Cloud Computing and Resource Management
