Verifiable credentials are a digital analogue of physical credentials. Their authenticity and integrity are protected by means of cryptographic techniques, and they can be presented to verifiers to reveal attributes or even predicates about the attributes included in the credential. One way to preserve privacy during presentation consists in selectively disclosing the attributes in a credential. In this paper we present the most widespread cryptographic mechanisms used to enable selective disclosure of attributes identifying two categories: the ones based on hiding commitments - e.g., mdl ISO/IEC 18013-5 - and the ones based on non-interactive zero-knowledge proofs - e.g., BBS signatures. We also include a description of the cryptographic primitives used to design such cryptographic mechanisms. We describe the design of the cryptographic mechanisms and compare them by performing an analysis on their standard maturity in terms of standardization, cryptographic agility and quantum safety, then we compare the features that they support with main focus on the unlinkability of presentations, the ability to create predicate proofs and support for threshold credential issuance. Finally we perform an experimental evaluation based on the Rust open source implementations that we have considered most relevant. In particular we evaluate the size of credentials and presentations built using different cryptographic mechanisms and the time needed to generate and verify them. We also highlight some trade-offs that must be considered in the instantiation of the cryptographic mechanisms.
COD-ssi: Enforcing Mutual Privacy for Credential Oblivious Disclosure in Self Sovereign Identity
King Abdullah University of Science and Technology (KAUST)(阿卜杜拉国王科技大学);Institute of Applied Sciences and Intelligent Systems (ISASI), National Research Council of Italy (CNR)(意大利国家研究委员会应用科学与智能系统研究所);Istituto di Informatica e Telematica (IIT)(信息与电信研究所);Department of Computer Science, National Research Council of Italy (CNR), University of Pisa(比萨大学计算机系,意大利国家研究委员会)
Trustworthy Blockchain-based Federated Learning for Electronic Health Records: Securing Participant Identity with Decentralized Identifiers and Verifiable Credentials
Federal Institute of Education, Science, and Technology of Rio Grande do Norte (IFRN)(里约格兰德北教育科学和技术联邦学院)