Efficient Zero-Knowledge Proofs for Set Membership in Blockchain-Based Sensor Networks: A Novel OR-Aggregation Approach

TL;DR

This paper presents a novel OR-aggregation method for zero-knowledge set membership proofs, enhancing efficiency and scalability in blockchain-based sensor networks, especially for resource-constrained IoT devices.

Contribution

It introduces a new OR-aggregation approach with theoretical foundations, optimized protocols, and security analysis tailored for blockchain IoT environments.

Findings

Significant reduction in proof size, generation time, and verification effort.

Demonstrated scalability and efficiency improvements over existing methods.

Validated effectiveness through extensive experimental evaluation.

Abstract

Blockchain-based sensor networks offer promising solutions for secure and transparent data management in IoT ecosystems. However, efficient set membership proofs remain a critical challenge, particularly in resource-constrained environments. This paper introduces a novel OR-aggregation approach for zero-knowledge set membership proofs, tailored specifically for blockchain-based sensor networks. We provide a comprehensive theoretical foundation, detailed protocol specification, and rigorous security analysis. Our implementation incorporates optimization techniques for resource-constrained devices and strategies for integration with prominent blockchain platforms. Extensive experimental evaluation demonstrates the superiority of our approach over existing methods, particularly for large-scale deployments. Results show significant improvements in proof size, generation time, and verification efficiency. The proposed OR-aggregation technique offers a scalable and privacy-preserving solution for set membership verification in blockchain-based IoT applications, addressing key limitations of current approaches. Our work contributes to the advancement of efficient and secure data management in large-scale sensor networks, paving the way for wider adoption of blockchain technology in IoT ecosystems.