On Cryptographic Mechanisms for the Selective Disclosure of Verifiable Credentials
- URL: http://arxiv.org/abs/2401.08196v1
- Date: Tue, 16 Jan 2024 08:22:28 GMT
- Title: On Cryptographic Mechanisms for the Selective Disclosure of Verifiable Credentials
- Authors: Andrea Flamini, Giada Sciarretta, Mario Scuro, Amir Sharif, Alessandro Tomasi, Silvio Ranise,
- Abstract summary: Verifiable credentials are a digital analogue of physical credentials.
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.
- Score: 39.4080639822574
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: 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.
Related papers
- DePrompt: Desensitization and Evaluation of Personal Identifiable Information in Large Language Model Prompts [11.883785681042593]
DePrompt is a desensitization protection and effectiveness evaluation framework for prompt.
We integrate contextual attributes to define privacy types, achieving high-precision PII entity identification.
Our framework is adaptable to prompts and can be extended to text usability-dependent scenarios.
arXiv Detail & Related papers (2024-08-16T02:38:25Z) - Towards Credential-based Device Registration in DApps for DePINs with ZKPs [46.08150780379237]
We propose a credential-based device registration (CDR) mechanism that verifies device credentials on the blockchain.
We present a general system model, and technically evaluate CDR using zkSNARKs with Groth16 and Marlin.
arXiv Detail & Related papers (2024-06-27T09:50:10Z) - Selective disclosure of claims from multiple digital credentials [0.0]
This paper presents a novel approach to selective disclosure that combines Merkle hash trees and Boneh-Lynn-Shacham signatures.
Besides selective disclosure, we enable issuing credentials signed by multiple issuers using this approach.
arXiv Detail & Related papers (2024-02-23T17:20:28Z) - Asynchronous Authentication [3.038642416291856]
Digital asset heists and identity theft cases illustrate the urgent need to revisit the fundamentals of user authentication.
We formalize the general, common case of asynchronous authentication, with unbounded message propagation time.
Our model allows for eventual message delivery, while bounding execution time to maintain cryptographic guarantees.
arXiv Detail & Related papers (2023-12-21T15:53:54Z) - HFORD: High-Fidelity and Occlusion-Robust De-identification for Face
Privacy Protection [60.63915939982923]
Face de-identification is a practical way to solve the identity protection problem.
The existing facial de-identification methods have revealed several problems.
We present a High-Fidelity and Occlusion-Robust De-identification (HFORD) method to deal with these issues.
arXiv Detail & Related papers (2023-11-15T08:59:02Z) - Redactable Signature Schemes and Zero-knowledge Proofs: A comparative examination for applications in Decentralized Digital Identity Systems [8.501327327617313]
Redactable Signature Schemes and Zero-Knowledge Proofs are two radically different approaches to enable privacy.
This paper analyses their merits and drawbacks when applied to decentralized identity system.
arXiv Detail & Related papers (2023-10-24T15:30:33Z) - Conditional Generative Adversarial Network for keystroke presentation
attack [0.0]
We propose to study a new approach aiming to deploy a presentation attack towards a keystroke authentication system.
Our idea is to use Conditional Generative Adversarial Networks (cGAN) for generating synthetic keystroke data that can be used for impersonating an authorized user.
Results indicate that the cGAN can effectively generate keystroke dynamics patterns that can be used for deceiving keystroke authentication systems.
arXiv Detail & Related papers (2022-12-16T12:45:16Z) - Properties from Mechanisms: An Equivariance Perspective on Identifiable
Representation Learning [79.4957965474334]
Key goal of unsupervised representation learning is "inverting" a data generating process to recover its latent properties.
This paper asks, "Can we instead identify latent properties by leveraging knowledge of the mechanisms that govern their evolution?"
We provide a complete characterization of the sources of non-identifiability as we vary knowledge about a set of possible mechanisms.
arXiv Detail & Related papers (2021-10-29T14:04:08Z) - PASS: Protected Attribute Suppression System for Mitigating Bias in Face
Recognition [55.858374644761525]
Face recognition networks encode information about sensitive attributes while being trained for identity classification.
Existing bias mitigation approaches require end-to-end training and are unable to achieve high verification accuracy.
We present a descriptors-based adversarial de-biasing approach called Protected Attribute Suppression System ( PASS)'
Pass can be trained on top of descriptors obtained from any previously trained high-performing network to classify identities and simultaneously reduce encoding of sensitive attributes.
arXiv Detail & Related papers (2021-08-09T00:39:22Z) - Open-set Adversarial Defense [93.25058425356694]
We show that open-set recognition systems are vulnerable to adversarial attacks.
Motivated by this observation, we emphasize the need of an Open-Set Adrial Defense (OSAD) mechanism.
This paper proposes an Open-Set Defense Network (OSDN) as a solution to the OSAD problem.
arXiv Detail & Related papers (2020-09-02T04:35:33Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.