Autor según el artículo: Sánchez, D. Batet, M. Viejo, A.
Versión del articulo depositado: info:eu-repo/semantics/submittedVersion
Departamento: Enginyeria Informàtica i Matemàtiques
URL Documento de licencia: https://repositori.urv.cat/ca/proteccio-de-dades/
Resumen: Text sanitization is crucial to enable privacy-preserving declassification of confidential documents. Moreover, considering the advent of new information sharing technologies that enable the daily publication of thousands of textual documents, automatic and semi-automatic sanitization methods are needed. Even though several of these methods have been proposed, most of them detect and sanitize sensitive terms (e.g., people names, addresses, diseases, etc.) independently, neglecting the importance of semantic correlations. From the attacker’s perspective, semantic correlations can be exploited to disclose a sanitized term from the presence of one or several non-sanitized words. To tackle this problem, this paper presents a general-purpose method that, by taking the output of a standard sanitization mechanism, analyses, detects and proposes for sanitization those semantically correlated terms that represent a plausible disclosure risk for the already sanitized ones. Our method relies on an information-theoretic formulation of disclosure risk which is able to adapt its behavior to the criterion of the initial sanitizer. The evaluation, carried on over a collection of real documents, shows that semantic correlations represent a real privacy threat in prior sanitized documents, and that our method is able to detect them effectively. As a result, the disclosure risk of the sanitized output is significantly reduced with respect to standard sanitization mechanisms.
Entidad: Universitat Rovira i Virgili.
Año de publicación de la revista: 2013
Acceso a la licencia de uso: https://creativecommons.org/licenses/by/3.0/es/
ISSN: 0020-0255
Página inicial: 110
Página final: 123
Volumen de revista: 249
Repositori URV