Author, as appears in the article.: Josep Domingo-Ferrer; Krishnamurty Muralidhar; Maria Bras-Amorós

Department: Enginyeria Informàtica i Matemàtiques

URV's Author/s: Bras Amoros, Maria / Domingo Ferrer, Josep

Keywords: Privacy Correlation-coefficients utility statistical disclosure control sets permutation model paradigm information loss data anonymization confidentiality anonymization anonymity

Abstract: 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 …

Thematic Areas: 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

licence for use: https://creativecommons.org/licenses/by/3.0/es/

Author's mail: josep.domingo@urv.cat maria.bras@urv.cat

Author identifier: 0000-0001-7213-4962 0000-0002-3481-004X

Record's date: 2023-02-19

Papper version: info:eu-repo/semantics/acceptedVersion

Link to the original source: https://www.computer.org/csdl/journal/tq/5555/01/08966490/1gNEMChWNIk

Licence document URL: http://repositori.urv.cat/ca/proteccio-de-dades/

Papper original source: Ieee Transactions On Dependable And Secure Computing. 18 (5): 2506-2517

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

Article's DOI: 10.1109/TDSC.2020.2968027

Entity: Universitat Rovira i Virgili

Journal publication year: 2021

Publication Type: Journal Publications