首页|Simulation extractable SNARKs based on target linearly collision-resistant oracle

Simulation extractable SNARKs based on target linearly collision-resistant oracle

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The famous zero-knowledge succinct non-interactive arguments of knowledge(zk-SNARK)was proposed by Groth in 2016.Typically,the construction is based on quadratic arithmetic programs which are highly efficient concerning the proof length and the verification complexity.Since then,there has been much progress in designing zk-SNARKs,achieving stronger security,and simulated extractability,which is analogous to non-malleability and has broad applications.In this study,following Groth's pairing-based zk-SNARK,a simulation extractability zk-SNARK under the random oracle model is constructed.Our construction relies on a newly proposed property named target linearly collision-resistant,which is satisfied by random oracles under discrete logarithm assumptions.Compared to the original Groth 16 zk-SNARK,in our construction,both parties are allowed to use such a random oracle,aiming to get the same random number.The resulting proof consists of 3 group elements and only 1 pairing equation needs to be verified.Compared to other related works,our construction is shorter in proof length and simpler in verification while preserving simulation extractability.The results also extend to achieve subversion zero-knowledge SNARKs.

quadratic arithmetic programsimulation extractabilitysubversion zero-knowledgesuccinct non-interactive arguments of knowledgetarget linearly collision-resistant

WANG LiGuan、LI Yuan、ZHANG ShuangJun、CAI DongLiang、KAN HaiBin

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Shanghai Key Laboratory of Intelligent Information Processing,School of Computer Science,Fudan University,Shanghai 200433,China

Shanghai Engineering Research Center of Blockchain,Shanghai 200433,China

Yiwu Research Institute of Fudan University,Yiwu 322000,China

National Key R&D Program of ChinaNational Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaInnovation Action Plan of Shanghai Science and TechnologyKey R&D Program of Guangdong Province

2019YFB210170362272107U19A2066215111022002020B0101090001

2024

10.1007/s11431-023-2580-5

中国科学:技术科学(英文版)
中国科学院

中国科学:技术科学(英文版)

CSTPCDEI
影响因子：1.056
ISSN：1674-7321
年,卷(期)：2024.67(9)