Uncoordinated syntactic privacy: a new composable metric for multiple, independent data publishing

A privacy model is a privacy condition, dependent on a parameter, that guarantees an upper bound on the risk of reidentification disclosure and maybe also on the risk of attribute disclosure by an adversary. A privacy model is composable if the privacy guarantees of the model are preserved, possibly...

Descripción completa

Detalles Bibliográficos
Autores: Tobar Nicolau, Adrián|||0000-0003-0198-2475, Parra Arnau, Javier|||0000-0002-1772-1088, Forné Muñoz, Jorge|||0000-0002-8401-3292, Torra, Vicenç
Tipo de recurso: artículo
Fecha de publicación:2025
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/427754
Acceso en línea:https://hdl.handle.net/2117/427754
https://dx.doi.org/10.1109/TIFS.2025.3551645
Access Level:acceso abierto
Palabra clave:Privacy
Data privacy
Syntactics
Data models
Publishing
Semantics
Degradation
Databases
Protection
Proposals
Privacy model
Composability property
Syntactic privacy
Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Telemàtica i xarxes d'ordinadors
id ES_5243b1b5bfa2d41dacb5359775e45cb6
oai_identifier_str oai:upcommons.upc.edu:2117/427754
network_acronym_str ES
network_name_str España
repository_id_str
dc.title.none.fl_str_mv Uncoordinated syntactic privacy: a new composable metric for multiple, independent data publishing
title Uncoordinated syntactic privacy: a new composable metric for multiple, independent data publishing
spellingShingle Uncoordinated syntactic privacy: a new composable metric for multiple, independent data publishing
Tobar Nicolau, Adrián|||0000-0003-0198-2475
Privacy
Data privacy
Syntactics
Data models
Publishing
Semantics
Degradation
Databases
Protection
Proposals
Data privacy
Privacy model
Composability property
Syntactic privacy
Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Telemàtica i xarxes d'ordinadors
title_short Uncoordinated syntactic privacy: a new composable metric for multiple, independent data publishing
title_full Uncoordinated syntactic privacy: a new composable metric for multiple, independent data publishing
title_fullStr Uncoordinated syntactic privacy: a new composable metric for multiple, independent data publishing
title_full_unstemmed Uncoordinated syntactic privacy: a new composable metric for multiple, independent data publishing
title_sort Uncoordinated syntactic privacy: a new composable metric for multiple, independent data publishing
dc.creator.none.fl_str_mv Tobar Nicolau, Adrián|||0000-0003-0198-2475
Parra Arnau, Javier|||0000-0002-1772-1088
Forné Muñoz, Jorge|||0000-0002-8401-3292
Torra, Vicenç
author Tobar Nicolau, Adrián|||0000-0003-0198-2475
author_facet Tobar Nicolau, Adrián|||0000-0003-0198-2475
Parra Arnau, Javier|||0000-0002-1772-1088
Forné Muñoz, Jorge|||0000-0002-8401-3292
Torra, Vicenç
author_role author
author2 Parra Arnau, Javier|||0000-0002-1772-1088
Forné Muñoz, Jorge|||0000-0002-8401-3292
Torra, Vicenç
author2_role author
author
author
dc.subject.none.fl_str_mv Privacy
Data privacy
Syntactics
Data models
Publishing
Semantics
Degradation
Databases
Protection
Proposals
Data privacy
Privacy model
Composability property
Syntactic privacy
Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Telemàtica i xarxes d'ordinadors
topic Privacy
Data privacy
Syntactics
Data models
Publishing
Semantics
Degradation
Databases
Protection
Proposals
Data privacy
Privacy model
Composability property
Syntactic privacy
Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Telemàtica i xarxes d'ordinadors
description A privacy model is a privacy condition, dependent on a parameter, that guarantees an upper bound on the risk of reidentification disclosure and maybe also on the risk of attribute disclosure by an adversary. A privacy model is composable if the privacy guarantees of the model are preserved, possibly to a limited extent, after repeated independent application of the privacy model. From the opposite perspective, a privacy model is not composable if multiple independent data releases, each of them satisfying the requirements of the privacy model, may result in a privacy breach. Current privacy models are broadly classified into syntactic ones (such as k-anonymity and l-diversity) and semantic ones, which essentially refer to e -differential privacy (e-DP) and variations thereof. While e-DP and its variants offer strong composability properties, syntactic notions are not composable unless data releases are conducted by a single, centralized data holder that uses specialized notions such as m-invariance and t -safety. In this work, we propose m-uncoordinated-syntactic-privacy (m-USP), the first syntactic notion with composability properties for the independent publication of nondisjoint data, in other words, without a centralized data holder. Theoretical results are formally proven, and experimental results demonstrate that the risk to individuals does not increase significantly, in contrast to non-composable methods, that are susceptible to attribute disclosure. In most cases, the utility degradation caused by the extra protection is less than 5% and decreases as the value of m increases.
publishDate 2025
dc.date.none.fl_str_mv 2025
2025-03-14
2025
2025-04-08
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/2117/427754
https://dx.doi.org/10.1109/TIFS.2025.3551645
url https://hdl.handle.net/2117/427754
https://dx.doi.org/10.1109/TIFS.2025.3551645
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.relation.none.fl_str_mv Agencia Estatal de Investigación http://doi.org/10.13039/501100011033 Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023 PID2023-148716OB-C32 DISCOVERY: PROTOCOLOS EN REDES DE COMUNICACIONES Y PRIVACIDAD DE DATOS
Agencia Estatal de Investigación http://doi.org/10.13039/501100011033 Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020 PID2020-113795RB-C31 COMPROMISE. PRIVACIDAD DE DATOS PARA REDES DE COMUNICACIONES Y BASES DE DATOS DINAMICAS
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:UPCommons. Portal del coneixement obert de la UPC
instname:Universitat Politècnica de Catalunya (UPC)
instname_str Universitat Politècnica de Catalunya (UPC)
reponame_str UPCommons. Portal del coneixement obert de la UPC
collection UPCommons. Portal del coneixement obert de la UPC
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1869408019811401728
spelling Uncoordinated syntactic privacy: a new composable metric for multiple, independent data publishingTobar Nicolau, Adrián|||0000-0003-0198-2475Parra Arnau, Javier|||0000-0002-1772-1088Forné Muñoz, Jorge|||0000-0002-8401-3292Torra, VicençPrivacyData privacySyntacticsData modelsPublishingSemanticsDegradationDatabasesProtectionProposalsData privacyPrivacy modelComposability propertySyntactic privacyÀrees temàtiques de la UPC::Enginyeria de la telecomunicació::Telemàtica i xarxes d'ordinadorsA privacy model is a privacy condition, dependent on a parameter, that guarantees an upper bound on the risk of reidentification disclosure and maybe also on the risk of attribute disclosure by an adversary. A privacy model is composable if the privacy guarantees of the model are preserved, possibly to a limited extent, after repeated independent application of the privacy model. From the opposite perspective, a privacy model is not composable if multiple independent data releases, each of them satisfying the requirements of the privacy model, may result in a privacy breach. Current privacy models are broadly classified into syntactic ones (such as k-anonymity and l-diversity) and semantic ones, which essentially refer to e -differential privacy (e-DP) and variations thereof. While e-DP and its variants offer strong composability properties, syntactic notions are not composable unless data releases are conducted by a single, centralized data holder that uses specialized notions such as m-invariance and t -safety. In this work, we propose m-uncoordinated-syntactic-privacy (m-USP), the first syntactic notion with composability properties for the independent publication of nondisjoint data, in other words, without a centralized data holder. Theoretical results are formally proven, and experimental results demonstrate that the risk to individuals does not increase significantly, in contrast to non-composable methods, that are susceptible to attribute disclosure. In most cases, the utility degradation caused by the extra protection is less than 5% and decreases as the value of m increases.Javier Parra-Arnau is the recipient of a “Ram´ on y Cajal” fellowship (ref. RYC2021-034256-I) funded by the Spanish Ministry of Science and Innovation and the European Union– “NextGenerationEU”/PRTR (Plan de Recuperaci´ on, Transformaci´ on y Resiliencia). This work was also supported by the Spanish Government under the following projects: ”DIstributed Smart Communications with Verifiable EneRgy-optimal Yields (DISCOVERY)” PID2023-148716OB-C32, funded by MCIN/AEI/10.13039/501100011033; “Enhancing Communication Protocols with Machine Learning while Protecting Sensitive Data (COMPROMISE)” PID2020-113795RBC31, funded by MICIU/AEI/10.13039/501100011033; and “Anonymization technology for AI-based analytics of mobility data (MOBILYTICS)” (TED2021-129782B-I00), funded by MICIU/AEI/10.13039/501100011033 and by the European Union NextGenerationEU/PRTR. This work was also partially funded by the Generalitat de Catalunya, under AGAUR grant “2021 SGR 01413”; was partially supported by the Wallenberg AI, Autonomous Systems and Software Program (WASP) funded by the Knut and Alice Wallenberg Foundation; and received support by the project ”Privacy for complex data” (VR 2022-04645).20252025-03-1420252025-04-08journal articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/2117/427754https://dx.doi.org/10.1109/TIFS.2025.3551645reponame:UPCommons. Portal del coneixement obert de la UPCinstname:Universitat Politècnica de Catalunya (UPC)InglésengAgencia Estatal de Investigación http://doi.org/10.13039/501100011033 Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023 PID2023-148716OB-C32 DISCOVERY: PROTOCOLOS EN REDES DE COMUNICACIONES Y PRIVACIDAD DE DATOSAgencia Estatal de Investigación http://doi.org/10.13039/501100011033 Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020 PID2020-113795RB-C31 COMPROMISE. PRIVACIDAD DE DATOS PARA REDES DE COMUNICACIONES Y BASES DE DATOS DINAMICASopen accesshttp://purl.org/coar/access_right/c_abf2Attribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:upcommons.upc.edu:2117/4277542026-05-27T15:37:01Z
score 15,812429

Similares en LA Referencia