Identity-based threshold (multi) signature with private accountability for privacy-preserving blockchain

Abstract

Identity-based threshold signature (IDTHS) allows a threshold number of signers to generate signatures to improve the deterministic wallet in the blockchain. However, the IDTHS scheme cannot determine the identity of malicious signers in case of misinformation. To solve this challenge, we propose an identity-based threshold (multi) signature with private accountability (for short AIDTHS) for privacy-preserving blockchain. From the public perspective, AIDTHS is completely private and no user knows who participated in generating the signature. At the same time, when there is a problem with the transaction, a trace entity can trace and be accountable to the signers. We formally define the syntax and security model of AIDTHS. To address the issue of identifying malicious signers, we improve upon traditional identity-based threshold signatures by incorporating zero-knowledge proofs as part of the signature and leveraging a tracer holding tracing keys to identify all signers. Additionally, to protect the privacy of signers, the signature is no longer achievable by anyone, which requires a combiner holding the keys to produce a valid signature. We give a concrete construction of AIDTHS and prove its security. Finally, we implement the AIDTHS scheme and compare it with existing schemes. The key distribution algorithm of AIDTHS takes 13.04 ms and the signature algorithm takes 34.60 μs. The verification algorithm takes 1 s, which is one-third of the time the TAPS scheme uses.

Keywords

Identity-based signature / Threshold (multi) signature / Accountability / Blockchain

CRediT authorship contribution statement

Jing Tian: Writing - original draft. Yanqi Zhao: Writing - original draft. Xiaoyi Yang: Writing - review & editing. Xuan Zhao: Formal analysis, Data curation. Ruonan Chen: Writing - original draft. Yong Yu: Writing - review & editing.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments

This work was supported by the National Key R & D Program of China (2022YFB2701500), the National Natural Science Foundation of China (62272385, 62202375), Shaanxi Distinguished Youth Project, China (2022JC-47), the Major Program of Shandong Provincial Natural Science Foundation for the Fundamental Research, China under Grant (ZR2022ZD03), the Key Research and Development Program of Shaanxi, China (2024GX-ZDCYL-01-09, 2024GX-ZDCYL-01-15) and Young Talent Fund of Association for Science and Technology in Shaanxi, China (20220134).

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