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Privacy-Preserving Data Publishing: An Overview

Privacy preservation has become a major issue in many data analysis applications. When a data set is released to other parties for data analysis, privacy-preserving techniques are often required to reduce the possibility of identifying sensitive information about individuals. For example, in medical...

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Detalles Bibliográficos
Autores principales: Wong, Raymond Chi-Wing, Fu, Ada Wai-Chee
Lenguaje:eng
Publicado: Morgan & Claypool Publishers 2010
Materias:
Acceso en línea:http://cds.cern.ch/record/1486543
Descripción
Sumario:Privacy preservation has become a major issue in many data analysis applications. When a data set is released to other parties for data analysis, privacy-preserving techniques are often required to reduce the possibility of identifying sensitive information about individuals. For example, in medical data, sensitive information can be the fact that a particular patient suffers from HIV. In spatial data, sensitive information can be a specific location of an individual. In web surfing data, the information that a user browses certain websites may be considered sensitive. Consider a dataset conta