Privacy homomorphisms for statistical confidentiality.

Título inglés	Privacy homomorphisms for statistical confidentiality.
Título español	Homomorfismos de privacidad para la confidencialidad estadística.
Autor/es	Domingo i Ferrer, Josep
Organización	Estad. Inv. Oper. Dep. Eng. Quím. Univ. Rovira i Virgili, Tarragona, España
Revista	0210-8054
Publicación	1996, 20 (3): 505-521, 11 Ref.
Tipo de documento	articulo
Idioma	Inglés
Resumen inglés	When publishing contingency tables which contain official statistics, a need to preserve statistical confidentiality arises. Statistical disclosure of individual units must be prevented. There is a wide choice of techniques to achieve this anonymization: cell supression, cell perturbation, etc. In this paper, we tackle the problem of using anonymized data to compute exact statistics; our approach is based on privacy homomorphisms, which are encryption transformations such that the decryption of a function of cyphers is a (possibly different) function of the corresponding clear messages. A new privacy homomorphism is presented and combined with some anonymization techniques, in order for a classified level to retrieve exact statistics from statistics computed on disclosure-protected data at an unclassified level.
Clasificación UNESCO	120308
Palabras clave español	Homomorfismos ; Protección de datos ; Protección informática ; Datos estadísticos ; Codificación de datos ; Criptología
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