Mirabi, Meghdad ; Binnig, Carsten (2023)
QFilter: Towards a Fine-Grained Access Control for Aggregation Query Processing over Secret Shared Data.
In: CEUR Workshop Proceedings, 3462
Artikel, Bibliographie
Kurzbeschreibung (Abstract)
This paper presents QFilter, a privacy-preserving and communication efficient solution that integrates an Attribute-Based Access Control (ABAC) model into query processing. QFilter enables the specification and enforcement of fine-grained access control policies tailored to secret-shared data. It can process aggregation SQL queries, including” count”,” sum”, and” avg” functions, with both conjunctive (using” AND”) and disjunctive (using” OR”) equality query conditions, without the need for inter-server communication. QFilter is secure against honest-but-curious adversaries, and the preliminary experiments illustrate its applicability for preserving privacy in query processing over secret-shared data, especially at the tuple level access control with the lowest overhead.
| Typ des Eintrags: | Artikel |
|---|---|
| Erschienen: | 2023 |
| Autor(en): | Mirabi, Meghdad ; Binnig, Carsten |
| Art des Eintrags: | Bibliographie |
| Titel: | QFilter: Towards a Fine-Grained Access Control for Aggregation Query Processing over Secret Shared Data |
| Sprache: | Englisch |
| Publikationsjahr: | 2023 |
| Verlag: | RWTH Aachen |
| Titel der Zeitschrift, Zeitung oder Schriftenreihe: | CEUR Workshop Proceedings |
| Jahrgang/Volume einer Zeitschrift: | 3462 |
| Band einer Reihe: | 3462 |
| URL / URN: | urn:nbn:de:0074-3462-7 |
| Zugehörige Links: | |
| Kurzbeschreibung (Abstract): | This paper presents QFilter, a privacy-preserving and communication efficient solution that integrates an Attribute-Based Access Control (ABAC) model into query processing. QFilter enables the specification and enforcement of fine-grained access control policies tailored to secret-shared data. It can process aggregation SQL queries, including” count”,” sum”, and” avg” functions, with both conjunctive (using” AND”) and disjunctive (using” OR”) equality query conditions, without the need for inter-server communication. QFilter is secure against honest-but-curious adversaries, and the preliminary experiments illustrate its applicability for preserving privacy in query processing over secret-shared data, especially at the tuple level access control with the lowest overhead. |
| Freie Schlagworte: | systems_funding_50100474, systems_bmwk_safefbdc |
| Zusätzliche Informationen: | Joint Proceedings of Workshops at the 49th International Conference on Very Large Data Bases (VLDB 2023), Vancouver, Canada, 28.08.-01.09.2023 |
| Fachbereich(e)/-gebiet(e): | 20 Fachbereich Informatik 20 Fachbereich Informatik > Data and AI Systems |
| Hinterlegungsdatum: | 03 Apr 2024 13:32 |
| Letzte Änderung: | 03 Apr 2024 13:32 |
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| Zugehörige Links: | |
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