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Título

An evolutionary approach to enhance data privacy

AutorJimenez, Javier; Mares, Jordi; Torra, Vicenç
Palabras claveData privacy
Disclosure risk
Risk assessment
Information privacy and security
Evolutionary algorithms
Fecha de publicación2011
EditorSpringer
CitaciónSoft Computing 15: 1301- 1311 (2011)
ResumenDissemination of data with sensitive information about individuals has an implicit risk of unauthorized disclosure. Perturbative masking methods propose the distortion of the original data sets before publication, tackling a difficult tradeoff between data utility (low information loss) and protection against disclosure (low disclosure risk). In this paper, we describe how information loss and disclosure risk measures can be integrated within an evolutionary algorithm to seek new and enhanced masking protections for continuous microdata. The proposed technique constitutes a hybrid approach that combines state-of-the-art protection methods with an evolutionary algorithm optimization. We also provide experimental results using three data sets in order to illustrate and empirically evaluate the application of this technique. © 2010 Springer-Verlag.
URIhttp://hdl.handle.net/10261/138201
DOI10.1007/s00500-010-0672-1
Identificadoresdoi: 10.1007/s00500-010-0672-1
issn: 1432-7643
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