Repositori institucional URV
| URV's Author/s: | Domingo Ferrer, Josep / Martinez Lluis, Sergio |
| Author, as appears in the article.: | Domingo-Ferrer, Josep; Muralidhar, Krishnamurty; Martinez, Sergio |
| Author's mail: | josep.domingo@urv.cat sergio.martinezl@urv.cat |
| Author identifier: | 0000-0001-7213-4962 0000-0002-3941-5348 |
| Journal publication year: | 2025 |
| Publication Type: | Journal Publications |
| APA: | Domingo-Ferrer, Josep; Muralidhar, Krishnamurty; Martinez, Sergio (2025). Synthetic Data Generation via the Permutation Paradigm With Optional k-Anonymity. Ieee Transactions On Dependable And Secure Computing, 22(3), 3155-3165. DOI: 10.1109/tdsc.2024.3525149 |
| Paper original source: | Ieee Transactions On Dependable And Secure Computing. 22 (3): 3155-3165 |
| Abstract: | Most methods in the literature on synthetic microdata (individual records) generation are parametric, that is, they require knowing or estimating the joint or the conditional distribution of the original microdata. This may be a significant hurdle unless the original microdata are multivariate normal. We propose a rank-based approach to generating synthetic microdata based on the permutation paradigm. We present three different methods and we analyze the utility and the confidentiality they afford. The third method is actually an extension of the second method that adds k-anonymity protection against reidentification to the confidentiality against attribute disclosure offered by the first two methods. Our algorithms only require the identification of the marginal distributions of attributes and yield synthetic attributes that replicate the relationships between the original attributes exclusively based on ranks. This proposal is especially attractive for non-normal or multi-type microdata. |
| Article's DOI: | 10.1109/tdsc.2024.3525149 |
| Link to the original source: | https://ieeexplore.ieee.org/document/10820070 |
| Paper version: | info:eu-repo/semantics/publishedVersion |
| licence for use: | https://creativecommons.org/licenses/by/3.0/es/ |
| Department: | Enginyeria Informàtica i Matemàtiques |
| Licence document URL: | https://repositori.urv.cat/ca/proteccio-de-dades/ |
| Thematic Areas: | Ciência da computação Computer science (all) Computer science (miscellaneous) Computer science, hardware & architecture Computer science, information systems Computer science, software engineering Electrical and electronic engineering Engenharias iii Engenharias iv General computer science |
| Keywords: | Anonymizatio Anonymization Computational modeling Confidentiality Covariance matrices Data models Data privacy Data protection Differential privacy Disclosure risk assessment Informatio Measurement Noise Peace, justice and strong institutions Permutation paradigm Prediction algorithms Privacy Proposals Protection Synthetic data Utility |
| Entity: | Universitat Rovira i Virgili |
| Record's date: | 2025-05-24 |
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