Autor segons l'article: Josep Domingo-Ferrer; Krishnamurty Muralidhar; Maria Bras-Amorós
Departament: Enginyeria Informàtica i Matemàtiques
Autor/s de la URV: Bras Amoros, Maria / Domingo Ferrer, Josep
Paraules clau: Privacy Correlation-coefficients utility statistical disclosure control sets permutation model paradigm information loss data anonymization confidentiality anonymization anonymity
Resum: Anonymization for privacy-preserving data publishing, also known as statistical disclosure control (SDC), can be viewed under the lens of the permutation model. According to this model, any SDC method for individual data records is functionally equivalent to a permutation step plus a noise addition step, where the noise added is marginal, in the sense that it does not alter ranks. Here, we propose metrics to quantify the data confidentiality and utility achieved by SDC methods based on the permutation model. We distinguish two privacy notions: in our work, anonymity refers to subjects and hence mainly to protection against record re-identification, whereas confidentiality refers to the protection afforded to attribute values against attribute disclosure. Thus, our confidentiality metrics are useful even if using a privacy model ensuring an anonymity level ex ante. The utility metric is a general-purpose metric that can be …
Àrees temàtiques: General computer science Engenharias iv Engenharias iii Electrical and electronic engineering Computer science, software engineering Computer science, information systems Computer science, hardware & architecture Computer science (miscellaneous) Computer science (all) Ciência da computação
Accès a la llicència d'ús: https://creativecommons.org/licenses/by/3.0/es/
Adreça de correu electrònic de l'autor: maria.bras@urv.cat josep.domingo@urv.cat
Identificador de l'autor: 0000-0002-3481-004X 0000-0001-7213-4962
Data d'alta del registre: 2024-07-27
Versió de l'article dipositat: info:eu-repo/semantics/acceptedVersion
Enllaç font original: https://www.computer.org/csdl/journal/tq/5555/01/08966490/1gNEMChWNIk
URL Document de llicència: https://repositori.urv.cat/ca/proteccio-de-dades/
Referència a l'article segons font original: Ieee Transactions On Dependable And Secure Computing. 18 (5): 2506-2517
Referència de l'ítem segons les normes APA: Josep Domingo-Ferrer; Krishnamurty Muralidhar; Maria Bras-Amorós (2021). General Confidentiality and Utility Metrics for Privacy-Preserving Data Publishing Based on the Permutation Model. Ieee Transactions On Dependable And Secure Computing, 18(5), 2506-2517. DOI: 10.1109/TDSC.2020.2968027
DOI de l'article: 10.1109/TDSC.2020.2968027
Entitat: Universitat Rovira i Virgili
Any de publicació de la revista: 2021
Tipus de publicació: Journal Publications
Repositori URV