Autor según el artículo: Maya-Lopez, Armando; Martinez-Balleste, Antoni; Casino, Fran
Departamento: Enginyeria Informàtica i Matemàtiques
Autor/es de la URV: Alkhoury, Nadine / Casino Cembellín, Francisco José / Martínez Ballesté, Antoni
Palabras clave: Travelling salesman problem Statistical disclosure control Microaggregation K-anonymity Data-oriented microaggregation Data protection Data privacy Algorithm
Resumen: The advent of decentralised systems and the continuous collection of personal data managed by public and private entities require the application of measures to guarantee the privacy of individuals. Due to the necessity to preserve both the privacy and the utility of such data, different techniques have been proposed in the literature. Microaggregation, a family of data perturbation methods, relies on the principle of k-anonymity to aggregate personal data records. While several microaggregation heuristics exist, those based on the Travelling Salesman Problem (TSP) have been shown to outperform the state of the art when considering the trade-off between privacy protection and data utility. However, TSP-based heuristics suffer from scalability issues. Intuitively, methods that may reduce the computational time of TSP-based heuristics may incur a higher information loss. Nevertheless, in this article, we propose a method that improves the performance of TSP-based heuristics and can be used in both small and large datasets effectively. Moreover, instead of focusing only on the computational time perspective, our method can preserve and sometimes reduce the information loss resulting from the microaggregation. Extensive experiments with different benchmarks show how our method is able to outperform the current state of the art, considering the trade-off between information loss and computational time.
Áreas temáticas: Química Operations research & management science Medicina iii Medicina ii Medicina i Materiais Matemática / probabilidade e estatística Interdisciplinar Geociências General engineering Farmacia Engineering, electrical & electronic Engineering (miscellaneous) Engineering (all) Engenharias iv Engenharias iii Engenharias ii Engenharias i Enfermagem Educação Economia Direito Computer science, artificial intelligence Computer science applications Ciências sociais aplicadas i Ciências biológicas iii Ciências biológicas ii Ciências biológicas i Ciências ambientais Ciências agrárias i Ciência da computação Biotecnología Biodiversidade Astronomia / física Artificial intelligence Arquitetura, urbanismo e design Administração, ciências contábeis e turismo Administração pública e de empresas, ciências contábeis e turismo
Acceso a la licencia de uso: https://creativecommons.org/licenses/by/3.0/es/
Direcció de correo del autor: franciscojose.casino@urv.cat nadine.alkhoury@estudiants.urv.cat nadine.alkhoury@estudiants.urv.cat nadine.alkhoury@estudiants.urv.cat nadine.alkhoury@estudiants.urv.cat antoni.martinez@urv.cat
Identificador del autor: 0000-0003-4296-2876 0000-0002-1787-7410
Fecha de alta del registro: 2024-10-12
Versión del articulo depositado: info:eu-repo/semantics/publishedVersion
Enlace a la fuente original: https://www.sciencedirect.com/science/article/pii/S0957417422019984
URL Documento de licencia: https://repositori.urv.cat/ca/proteccio-de-dades/
Referencia al articulo segun fuente origial: Expert Systems With Applications. 213 118980-
Referencia de l'ítem segons les normes APA: Maya-Lopez, Armando; Martinez-Balleste, Antoni; Casino, Fran (2023). A compression strategy for an efficient TSP-based microaggregation. Expert Systems With Applications, 213(), 118980-. DOI: 10.1016/j.eswa.2022.118980
DOI del artículo: 10.1016/j.eswa.2022.118980
Entidad: Universitat Rovira i Virgili
Año de publicación de la revista: 2023
Tipo de publicación: Journal Publications