HetDAPAC: Leveraging Attribute Heterogeneity in Distributed Attribute-Based Private Access Control
- URL: http://arxiv.org/abs/2511.11549v1
- Date: Fri, 14 Nov 2025 18:40:17 GMT
- Title: HetDAPAC: Leveraging Attribute Heterogeneity in Distributed Attribute-Based Private Access Control
- Abstract summary: Heterogeneous (Het)DAPAC is a framework which off-loads verification of $N-D$ of the $N$ attributes to a central server.<n>We propose a second scheme achieving a balanced per-server download and a rate of $frac12K$.
- Score: 43.914623898157856
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Verifying user attributes to provide fine-grained access control to databases is fundamental to attribute-based authentication. Either a single (central) authority verifies all the attributes, or multiple independent authorities verify the attributes distributedly. In the central setup, the authority verifies all user attributes, and the user downloads only the authorized record. While this is communication efficient, it reveals all user attributes to the authority. A distributed setup prevents this privacy breach by letting each authority verify and learn only one attribute. Motivated by this, Jafarpisheh~et~al. introduced an information-theoretic formulation, called distributed attribute-based private access control (DAPAC). With $N$ non-colluding authorities (servers), $N$ attributes and $K$ possible values for each attribute, the DAPAC system lets each server learn only the single attribute value that it verifies, and is oblivious to the remaining $N-1$. The user retrieves its designated record, without learning anything about the remaining database records. The goal is to maximize the rate, i.e., the ratio of desired message size to total download size. However, not all attributes are sensitive, and DAPAC's privacy constraints can be too restrictive, negatively affecting the rate. To leverage the heterogeneous privacy requirements of user attributes, we propose heterogeneous (Het)DAPAC, a framework which off-loads verification of $N-D$ of the $N$ attributes to a central server, and retains DAPAC's architecture for the $D$ sensitive attributes. We first present a HetDAPAC scheme, which improves the rate from $\frac{1}{2K}$ to $\frac{1}{K+1}$, while sacrificing the privacy of a few non-sensitive attributes. Unlike DAPAC, our scheme entails a download imbalance across servers; we propose a second scheme achieving a balanced per-server download and a rate of $\frac{D+1}{2KD}$.
Related papers
- A Tight Expressivity Hierarchy for GNN-Based Entity Resolution in Master Data Management [2.4366811507669115]
We prove a four-theorem separation theory on typed entity-attribute graphs.<n>For each predicate we prove tight bounds -- constructing graph pairs provably indistinguishable by every MPNN lacking the required adaptation.<n>Results yield a minimal-architecture principle: practitioners can select the cheapest sufficient adaptation set, with a guarantee that no simpler architecture works.
arXiv Detail & Related papers (2026-03-28T06:38:03Z) - TAPAS: Efficient Two-Server Asymmetric Private Aggregation Beyond Prio(+) [7.713377215066152]
We present TAPAS, a two-server asymmetric private aggregation scheme.<n>A key design choice is intentional asymmetry: one server bears the $O(L)$ aggregation and verification work, while the other operates as a lightweight facilitator.<n>We are the first to establish privacy and correctness with identifiable abort in the two-server setting.
arXiv Detail & Related papers (2026-03-20T13:52:09Z) - Lattice-Based Dynamic $k$-Times Anonymous Authentication [12.008179370101539]
$k$-times anonymous authentication ($k$-TAA) scheme allows members of a group to be authenticated anonymously by application providers up to $k$ times.<n>Considering quantum computing attacks, lattice-based $k$-TAA was introduced.<n>First lattice-based dynamic $k$-TAA offers limited times anonymous authentication, dynamic member management, and post-quantum security.
arXiv Detail & Related papers (2025-09-26T02:42:31Z) - Information-Theoretic Decentralized Secure Aggregation with Collusion Resilience [95.33295072401832]
We study the problem of decentralized secure aggregation (DSA) from an information-theoretic perspective.<n>We characterize the optimal rate region, which specifies the minimum achievable communication and secret key rates for DSA.<n>Our results establish the fundamental performance limits of DSA, providing insights for the design of provably secure and communication-efficient protocols.
arXiv Detail & Related papers (2025-08-01T12:51:37Z) - Frequency Estimation of Correlated Multi-attribute Data under Local Differential Privacy [5.258253745672122]
Local Differential Privacy (LDP) is a powerful tool to protect user data privacy.<n>Existing LDP mechanisms either split the privacy budget across all attributes or treat each attribute independently.<n>We propose Correlated Randomized Response (Corr-RR), a novel LDP mechanism that leverages correlations among attributes to substantially improve utility.
arXiv Detail & Related papers (2025-07-23T13:52:45Z) - Breaking the Gaussian Barrier: Residual-PAC Privacy for Automatic Privatization [27.430637970345433]
We show that the upper bound obtained by PAC Privacy algorithms is tight if and only if the perturbed mechanism output is jointly Gaussian with independent noise.<n>We introduce Residual-PAC (R-PAC) Privacy, an f-divergence-based measure to quantify privacy that remains after adversarial inference.<n>Our approach achieves efficient privacy budget utilization for arbitrary data distributions and naturally composes when multiple mechanisms access the dataset.
arXiv Detail & Related papers (2025-06-06T20:52:47Z) - An Approach for Handling Missing Attribute Values in Attribute-Based Access Control Policy Mining [0.0]
Attribute-Based Access Control (ABAC) enables highly expressive and flexible access decisions by considering a wide range of contextual attributes.<n>Algorithms that mine ABAC policies from legacy access control systems can significantly reduce the costs associated with migrating to ABAC.<n>This paper introduces an approach that enhances the policy mining process by predicting or inferring missing attribute values.
arXiv Detail & Related papers (2025-05-03T17:34:46Z) - HetDAPAC: Distributed Attribute-Based Private Access Control with Heterogeneous Attributes [35.16231062731263]
We show that off-loading a subset of attributes to a central server for verification improves the achievable rate from $frac12K$ in Jafarpisheh et al. to $frac1K+1$ in this paper.
arXiv Detail & Related papers (2024-01-24T18:48:28Z) - Guaranteeing Anonymity in Attribute-Based Authorization [3.2697504912958633]
Attribute-based methods make decisions based on attributes possessed by a subject rather than the subject's identity.
While this allows for anonymous authorization, it does not guarantee anonymity.
Other approaches to achieving anonymity in attribute-based authorization do not address this attribute distribution problem.
arXiv Detail & Related papers (2023-10-07T19:09:17Z) - Group Pose: A Simple Baseline for End-to-End Multi-person Pose
Estimation [102.02917299051757]
We present a simple yet effective transformer approach, named Group Pose.
We replace single self-attention over all the $Ntimes(K+1)$ queries with two subsequent group self-attentions.
Experimental results on MS COCO and CrowdPose show that our approach without human box supervision is superior to previous methods.
arXiv Detail & Related papers (2023-08-14T17:58:04Z) - MACSum: Controllable Summarization with Mixed Attributes [56.685735509260276]
MACSum is the first human-annotated summarization dataset for controlling mixed attributes.
We propose two simple and effective parameter-efficient approaches for the new task of mixed controllable summarization.
arXiv Detail & Related papers (2022-11-09T17:17:37Z) - AdaTag: Multi-Attribute Value Extraction from Product Profiles with
Adaptive Decoding [55.89773725577615]
We present AdaTag, which uses adaptive decoding to handle attribute extraction.
Our experiments on a real-world e-Commerce dataset show marked improvements over previous methods.
arXiv Detail & Related papers (2021-06-04T07:54:11Z)
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.