zkChain: An Efficient Blockchain Privacy Protection Scheme Based on zk-SNARKs

Huang, Jiahui; Huang, Teng; Zhang, Jiehua

doi:10.1007/978-3-031-20099-1_34

Cited by 2 publications

(3 citation statements)

References 11 publications

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“…All those studies cited in [57][58][59] did not focus on a DCMS scenario, unlike our proposal, which leverages zk-SNARKs in a blockchain-based DCMS. In our approach, zk-SNARKs play a crucial role in ensuring that patient data is securely stored on the blockchain without any reliance on the trustworthiness of the involved parties, i.e., DCs.…”

Section: Dcms Scenariomentioning

confidence: 95%

“…The blockchain can serve as a decentralized and distributed database, with all network participants having access to a copy of the data. Meanwhile, the current studies on zk-SNARKs have outlined the improved efficiency and robust privacy protection when using them with blockchain technology [57]. Huang et al [57] offered a method known as ZKchain, which uses zk-SNARKs in blockchain technology to improve privacy and efficiency.…”

Section: Dcms Scenariomentioning

confidence: 99%

“…Meanwhile, the current studies on zk-SNARKs have outlined the improved efficiency and robust privacy protection when using them with blockchain technology [57]. Huang et al [57] offered a method known as ZKchain, which uses zk-SNARKs in blockchain technology to improve privacy and efficiency. Additionally, zk-SNARKs have been successfully applied in developing Zcash, a cryptocurrency known for its robust privacy protections.…”

Section: Dcms Scenariomentioning

confidence: 99%

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Enhancing Data Protection in Dynamic Consent Management Systems: Formalizing Privacy and Security Definitions with Differential Privacy, Decentralization, and Zero-Knowledge Proofs

Khalid,

Ahmed,

Kim

2023

Sensors

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Dynamic consent management allows a data subject to dynamically govern her consent to access her data. Clearly, security and privacy guarantees are vital for the adoption of dynamic consent management systems. In particular, specific data protection guarantees can be required to comply with rules and laws (e.g., the General Data Protection Regulation (GDPR)). Since the primary instantiation of the dynamic consent management systems in the existing literature is towards developing sustainable e-healthcare services, in this paper, we study data protection issues in dynamic consent management systems, identifying crucial security and privacy properties and discussing severe limitations of systems described in the state of the art. We have presented the precise definitions of security and privacy properties that are essential to confirm the robustness of the dynamic consent management systems against diverse adversaries. Finally, under those precise formal definitions of security and privacy, we have proposed the implications of state-of-the-art tools and technologies such as differential privacy, blockchain technologies, zero-knowledge proofs, and cryptographic procedures that can be used to build dynamic consent management systems that are secure and private by design.

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Section: Dcms Scenariomentioning

confidence: 95%

Section: Dcms Scenariomentioning

confidence: 99%

Section: Dcms Scenariomentioning

confidence: 99%

See 1 more Smart Citation

Enhancing Data Protection in Dynamic Consent Management Systems: Formalizing Privacy and Security Definitions with Differential Privacy, Decentralization, and Zero-Knowledge Proofs

Khalid,

Ahmed,

Kim

2023

Sensors

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Promise of Zero‐Knowledge Proofs (ZKPs) for Blockchain Privacy and Security: Opportunities, Challenges, and Future Directions

Chirakarotu Nair,

Kumar Panakalapati

2024

Security and Privacy

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Blockchain technology has revolutionized data sharing and storage, yet maintaining privacy and security while ensuring transparency and immutability remains a significant challenge. This research addresses this challenge by investigating the promising solution of Zero‐Knowledge Proofs (ZKPs), which allow for validation without revealing additional information. Unlike previous studies that focus on specific ZKP types or limited performance metrics, this article provides a comprehensive analysis of multiple ZKP technologies, along with their distinct features and blockchain applications. We evaluate ZKP tools such as snarkjs, ZoKrates, and Circom, focusing on key factors including proof size, trusted setup, prover time, verifier time, and scalability. A detailed case study on the Ethereum blockchain demonstrates the practical implementation and performance of ZKPs, effectively bridging the gap between theoretical analysis and real‐world applications. Furthermore, we explore how ZKPs can significantly enhance scalability in blockchain applications. By proposing innovative ZKP use cases and addressing current challenges, this article not only provides a comprehensive understanding of ZKP technologies but also outlines potential future research directions, making a significant impact on the field of blockchain privacy and security.

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zkChain: An Efficient Blockchain Privacy Protection Scheme Based on zk-SNARKs

Cited by 2 publications

References 11 publications

Enhancing Data Protection in Dynamic Consent Management Systems: Formalizing Privacy and Security Definitions with Differential Privacy, Decentralization, and Zero-Knowledge Proofs

Enhancing Data Protection in Dynamic Consent Management Systems: Formalizing Privacy and Security Definitions with Differential Privacy, Decentralization, and Zero-Knowledge Proofs

Promise of Zero‐Knowledge Proofs (ZKPs) for Blockchain Privacy and Security: Opportunities, Challenges, and Future Directions

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