Quantum-Resistant Privacy-Preserving IoT Authentication via Zero-Knowledge Proofs and Blockchain Integration
Keywords:
IoT Security, Quantum-Resistant Cryptography, Zero-Knowledge Proofs, Blockchain, Privacy-Preserving Authentication, Homomorphic Encryption.
Abstract
IoT device authentication faces critical challenges in ensuring quantum resistance and privacy preservation while maintaining practical performance characteristics. This paper presents a novel privacy-preserving authentication framework that integrates blockchain technology, zero-knowledge proofs (ZKPs), and homomorphic encryption for secure IoT device management. Our approach uniquely combines Security Module operations with blockchain-based verification to address the limitations of the existing authentication methods through three key innovations: a lightweight post-quantum ZKP protocol, blockchain-based device verification with chameleon hash functions, and privacy-preserving homomorphic computation. In our experimental setup using an Intel Core i7 platform with simulated IoT sensor networks, the system achieves state-of-the-art performance with 350ms authentication times, a 5.7% improvement over current quantum-resistant solutions. The experimental results demonstrate robust scalability, supporting 100 concurrent simulated devices in a controlled test environment with 98% GUI responsiveness while maintaining privacy guarantees. The Security Module achieves 180ms homomorphic encryption times and 300ms/120ms for ZKP generation/verification, respectively. Through a novel blockchain integration framework, we further demonstrate gas efficiency with device registration averaging 145,000 gas units and 150ms network synchronization. The framework establishes practical quantum-resistant privacy-preserving authentication for IoT environments without compromising performance or scalability.
Published
2025-07-15
How to Cite
Tawfik, M., Abdelhaliem, A. H., & Fathi, I. (2025). Quantum-Resistant Privacy-Preserving IoT Authentication via Zero-Knowledge Proofs and Blockchain Integration. Statistics, Optimization & Information Computing. https://doi.org/10.19139/soic-2310-5070-2399
Issue
Section
Research Articles
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