Converting Fuzzy Signatures into Anonymizable Signatures using Zero-Knowledge Proof
Ken Naganuma, Shingo Akata, Masayuki Yoshino, Noboru Kunihiro, Non Kawana, Wataru Nakamura, Kenta Takahashi, Takayuki Suzuki · 2025
Management of secret keys for digital signatures is one of the most critical issues in decentralized applications. Since there is no administrator, losing a secret key can result in losing all assets or rights. To address this problem, fuzzy extractors and fuzzy signatures, which generate private keys directly from biometric information, have been considered in addition to conventional biometric authentication. However, these methods using biometric secret keys do not support group signatures. Therefore, it is not applicable to use cases that require consensus building by a specific community (group), such as DAO and DeFi.In this paper, we propose a new scheme for converting existing fuzzy signatures to group signatures using zero-knowledge proofs to address this problem. More precisely, we first define an anonymizable signature that is a generalization of a group signature and then convert a fuzzy signature into an anonymizable signature using an ordinary (classical) zero-knowledge proof. In addition, the signature data size is optimized to a constant size using zk-SNARK. Our implementation experiments show that our schemes achieve practical signature generation and verification times and signature sizes even for a group of up to 100,000 people. This paper’s results can be used to prevent the loss of secret keys and enable flexible DApps use cases.