bpK#: Delegatable Pseudonyms And Their Applications to National eID Systems
- URL: http://arxiv.org/abs/2605.30212v1
- Date: Thu, 28 May 2026 16:45:26 GMT
- Title: bpK#: Delegatable Pseudonyms And Their Applications to National eID Systems
- Abstract summary: Pseudonyms, as offered by Austria's governmental sector-specific personal identifiers (bPks), can significantly improve privacy.<n>The current architecture comes with several challenges regarding availability, privacy, and authenticity, due to a fully centralized design.<n>This paper proposes bPk#, a distributed architecture to address these issues, reducing reliance on the central authority.
- Score: 0.726437825413781
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Electronic identities (eIDs) are crucial in an increasingly digitalized environment. Pseudonyms, as offered by Austria's governmental sector-specific personal identifiers (bPks), can significantly improve privacy by ensuring that personal data is not universally traceable across public services and private companies. However, the current architecture comes with several challenges regarding availability, privacy, and authenticity, due to a fully centralized design. This paper proposes bPk#, a distributed architecture to address these issues, reducing reliance on the central authority, while still providing all functional requirements to the existing bPk system. In particular, users are delegated the rights to compute their own pseudonyms, thereby minimizing metadata revealed to the central authority, while (subsets of) service providers may receive the right to compute pseudonyms only within their own domain, thereby reducing the availability needs of the central authority. To the best of our knowledge, we provide the first formal framework for such delegatable pseudonym systems, together with a generic construction for which we provide formal security proofs. Furthermore, we propose a concrete instantiation of our construction, together with a reference implementation demonstrating the practical efficiency.
Related papers
- LLM Agents Enable User-Governed Personalization Beyond Platform Boundaries [44.615224255419484]
We argue for a shift from platform-centric personalization to user-governed personalization.<n>The key asymmetry lies in data access: only users can aggregate their own cross-platform and offline information.<n>We provide proof-of-concept evidence that users equipped with cross-platform data exports and an off-the-shelf LLM agent can outperform single-platform personalization baselines.
arXiv Detail & Related papers (2026-05-10T22:31:59Z) - From Hidden Profiles to Governable Personalization: Recommender Systems in the Age of LLM Agents [44.20821259751986]
We argue that the key issue is not simply that large language models can enhance recommendation quality, but that they mediate where and how user representations are produced, exposed, and acted upon.<n>We propose a shift from hidden platform profiling toward governable personalization, where user representations may become more inspectable, revisable, portable, and consequential across services.
arXiv Detail & Related papers (2026-04-22T00:04:47Z) - Interoperable Architecture for Digital Identity Delegation for AI Agents with Blockchain Integration [0.0]
We introduce a unified framework that enables bounded, auditable, and least-privilege delegation across heterogeneous identity ecosystems.<n>The framework includes four key elements: Delegation Grants (DGs), first-class authorization artefacts that encode revocable transfers of authority with enforced scope reduction.<n>It also includes a layered reference architecture that separates trust anchoring, credential and proof validation, policy evaluation, and protocol mediation via a Trust Gateway.
arXiv Detail & Related papers (2026-01-21T13:29:23Z) - Binding Agent ID: Unleashing the Power of AI Agents with accountability and credibility [46.323590135279126]
BAID (Binding Agent ID) is a comprehensive identity infrastructure establishing verifiable user-code binding.<n>We implement and evaluate a complete prototype system, demonstrating the practical feasibility of blockchain-based identity management and zkVM-based authentication protocol.
arXiv Detail & Related papers (2025-12-19T13:01:54Z) - Publicly Verifiable Private Information Retrieval Protocols Based on Function Secret Sharing [45.68069331331365]
Private Information Retrieval (PIR) is a cryptographic primitive that enables users to retrieve data from a database without revealing which item is being accessed.<n>We propose two effective constructions of publicly verifiable PIR (PVPIR) in the multi-server setting, which achieve query privacy, correctness, and verifiability simultaneously.
arXiv Detail & Related papers (2025-09-17T04:28:47Z) - An Architecture for Distributed Digital Identities in the Physical World [1.1303195606272813]
We design, analyze, and build a distributed digital identity architecture for physical world transactions.<n>This architecture combines (biometric and other) sensors, (established and upcoming) identity authorities, attribute verifiers, and a new core component we call the emphPersonal Identity Agent (PIA)<n>We present a first protocol between these parties and formally verify that it achieves relevant security properties based on a realistic threat model including strong global adversaries.
arXiv Detail & Related papers (2025-08-13T20:41:12Z) - SLVC-DIDA: Signature-less Verifiable Credential-based Issuer-hiding and Multi-party Authentication for Decentralized Identity [21.498265818902464]
Verifiable Credential techniques are used to facilitate decentralized DID-based access control across multiple entities.<n>Existing DID schemes generally rely on a distributed public key infrastructure that also causes challenges.<n>This paper proposes a Permanent-Hiding (PIH)-based DID-based multi-party authentication framework with a signature-less VC model, named SLVC-DIDA.
arXiv Detail & Related papers (2025-01-19T13:58:01Z) - Towards an identity management solution on Arweave [0.0]
This paper explores the potential of using Arweave network to develop an identity management solution.<n>By harnessing Arweave's permanent storage, our solution offers users Self-Sovereign Identity (SSI) framework.
arXiv Detail & Related papers (2024-12-18T14:01:31Z) - Balancing Confidentiality and Transparency for Blockchain-based Process-Aware Information Systems [43.253676241213626]
We propose an architecture for blockchain-based PAISs to preserve confidentiality and transparency.<n>Smart contracts enact, enforce and store public interactions, while attribute-based encryption techniques are adopted to specify access grants to confidential information.<n>We assess the security of our solution through a systematic threat model analysis and evaluate its practical feasibility.
arXiv Detail & Related papers (2024-12-07T20:18:36Z) - On the Compliance of Self-Sovereign Identity with GDPR Principles: A Critical Review [0.0]
Self-sovereign identity (SSI) was introduced as an IdM model to reduce the possibility of data breaches.
SSI is a decentralised IdM, where the data owner has sovereign control of personal data stored in their digital wallet.
This paper provides an evolution to IdMs and reviews state-of-the-art SSI frameworks.
arXiv Detail & Related papers (2024-09-05T15:35:53Z) - Combining Decentralized IDentifiers with Proof of Membership to Enable Trust in IoT Networks [44.99833362998488]
The paper proposes and discusses an alternative (mutual) authentication process for IoT nodes under the same administration domain.
The main idea is to combine the Decentralized IDentifier (DID)-based verification of private key ownership with the verification of a proof that the DID belongs to an evolving trusted set.
arXiv Detail & Related papers (2023-10-12T09:33:50Z) - Decentralised Learning from Independent Multi-Domain Labels for Person
Re-Identification [69.29602103582782]
Deep learning has been successful for many computer vision tasks due to the availability of shared and centralised large-scale training data.
However, increasing awareness of privacy concerns poses new challenges to deep learning, especially for person re-identification (Re-ID)
We propose a novel paradigm called Federated Person Re-Identification (FedReID) to construct a generalisable global model (a central server) by simultaneously learning with multiple privacy-preserved local models (local clients)
This client-server collaborative learning process is iteratively performed under privacy control, enabling FedReID to realise decentralised learning without sharing distributed data nor collecting any
arXiv Detail & Related papers (2020-06-07T13:32:33Z)
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.