A Privacy-Preserving Zero-Knowledge Proof for Blockchain

Chi, Po-Wen; Lu, Yun-Hsiu; Guan, Albert

doi:10.1109/access.2023.3302691

Cited by 8 publications

(4 citation statements)

References 37 publications

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“…In decentralized systems, ZKP caching can be implemented to store and reuse previously validated proofs, enhancing the efficiency. By caching ZKPs, systems can reduce the computational overhead of repeatedly generating or verifying the same proofs, leading to faster transaction times and optimized resource utilization while maintaining data privacy and security [17,18].…”

Section: Zero Knowledge Proofmentioning

confidence: 99%

“…This meticulous challenge response mechanism effectively bars unauthorized entities from accessing the data. Additionally, to enhance the efficiency, successful ZKP challenges and their corresponding responses are cached for future verifications [17].…”

Section: Zkp Challenge Generation and Cachingmentioning

confidence: 99%

“…Zero Knowledge Proof enables transactions or data validation without revealing the content, thus maintaining privacy and security [17,18]. Our system utilizes ZKP where a prover P can demonstrate the knowledge of a secret x corresponding to a statement S without disclosing x.…”

Section: Zero Knowledge Proof (Zkp)mentioning

confidence: 99%

“…Moreover, the system can result in cost savings by reducing the need for centralized data storage and processing centers and optimizing data transmission. An additional layer of privacy is introduced through the use of ZKP, ensuring that data can be verified without revealing their contents [17,18].…”

Section: Practical Implications and Use Casesmentioning

confidence: 99%

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Enhancing Industrial IoT Network Security through Blockchain Integration

Bobde,

Narayanan,

Jati

et al. 2024

Electronics

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In the rapidly evolving landscape of industrial ecosystems, Industrial IoT networks face increasing security challenges. Traditional security methods often struggle to protect these networks adequately, posing risks to data integrity, confidentiality, and access control. Our research introduces a methodology that leverages blockchain technology to enhance the security and trustworthiness of IoT networks. This approach starts with sensor nodes collecting and compressing data, followed by encryption using the ChaCha20-Poly1305 algorithm and transmission to local aggregators. A crucial element of our system is the private blockchain gateway, which processes and classifies data based on confidentiality levels, determining their storage in cloud servers or the Interplanetary File System for enhanced security. The system’s integrity and authenticity are further reinforced through the proof of authority consensus mechanism. This system employs Zero Knowledge Proof challenges for device authorization, optimizing data retrieval while maintaining a delicate balance between security and accessibility. Our methodology contributes to mitigating vulnerabilities in Industrial IoT networks and is part of a broader effort to advance the security and operational efficiency of these systems. It reflects an understanding of the diverse and evolving challenges in IoT security, emphasizing the need for continuous innovation and adaptation in this dynamic field.

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Section: Zero Knowledge Proofmentioning

confidence: 99%

Section: Zkp Challenge Generation and Cachingmentioning

confidence: 99%

Section: Zero Knowledge Proof (Zkp)mentioning

confidence: 99%

Section: Practical Implications and Use Casesmentioning

confidence: 99%

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