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Data Anonymization that Leads to the Most Accurate Estimates of Statistical Characteristics: Fuzzy-Motivated Approach
To preserve privacy, the original data points (with exact values) are replaced by boxes containing each (inaccessible) data point. This privacy-motivated uncertainty leads to uncertainty in the statistical characteristics computed based on this data. In a previous paper, we described how to minimize...
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| Main Authors: | , , , , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado: |
2013
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| Assuntos: | |
| Acceso en liña: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4150686/ https://ncbi.nlm.nih.gov/pubmed/25187183 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1109/IFSA-NAFIPS.2013.6608471 |
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