An Efficient Distributed Identity Selective Disclosure Algorithm
Guanzheng Wang, Guoyan Zhang · Applied Sciences · 2025
Distributed digital identity is an emerging identity management technology aimed at achieving comprehensive interconnectivity between digital objects. However, there is still the problem of privacy leakage in distributed identities, and selective disclosure technology partially solves the privacy issue in distributed identities. Most of the existing selective disclosure algorithms use anonymous credentials or hash functions. Anonymous credential schemes offer high security and meet the requirements of unforgeability and unlinkability, but their exponential operations result in low efficiency. The scheme based on hash functions, although more efficient, is susceptible to man-in-the-middle attacks. This article proposes an efficient selective disclosure scheme based on hash functions and implicit certificates. The attribute values are treated as leaf nodes of the Merkle tree, and the root node is placed in a verifiable credential. According to the implicit certificate algorithm process, a key pair that can use the credential is generated. During the attribute disclosure process, the user autonomously selects the attribute value to be presented and generates a verification path from the attribute to the root node. The verifier checks the Merkle tree verification path. All operations are completed within 10 ms while meeting the unforgeability requirements and resisting man-in-the-middle attacks. This article also utilizes the ZK-SNARK algorithm to hide the validation path of the Merkle tree, enhancing the security of the path during the disclosure process. The experimental results show that the selective disclosure algorithm performs well in both performance and privacy protection, with an efficiency 80% faster than that of existing schemes. This enhances the proposed scheme’s potential and value in the field of identity management; it also holds broad application prospects in fields such as the Internet of Things, finance, and others.