Articles producció científica> Enginyeria Informàtica i Matemàtiques

A compression strategy for an efficient TSP-based microaggregation

  • Dades identificatives

    Identificador: imarina:9286411
    Autors:
    Maya-Lopez, ArmandoMartinez-Balleste, AntoniCasino, Fran
    Resum:
    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.
  • Altres:

    Autor segons l'article: Maya-Lopez, Armando; Martinez-Balleste, Antoni; Casino, Fran
    Departament: Enginyeria Informàtica i Matemàtiques
    Autor/s de la URV: Alkhoury, Nadine / Casino Cembellín, Francisco José / Martínez Ballesté, Antoni
    Paraules clau: Travelling salesman problem Statistical disclosure control Microaggregation K-anonymity Data-oriented microaggregation Data protection Data privacy Algorithm
    Resum: 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.
    Àrees temàtiques: 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
    Accès a la llicència d'ús: https://creativecommons.org/licenses/by/3.0/es/
    Adreça de correu electrònic de l'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 de l'autor: 0000-0003-4296-2876 0000-0002-1787-7410
    Data d'alta del registre: 2024-10-12
    Versió de l'article dipositat: info:eu-repo/semantics/publishedVersion
    Enllaç font original: https://www.sciencedirect.com/science/article/pii/S0957417422019984
    URL Document de llicència: https://repositori.urv.cat/ca/proteccio-de-dades/
    Referència a l'article segons font original: Expert Systems With Applications. 213 118980-
    Referència 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 de l'article: 10.1016/j.eswa.2022.118980
    Entitat: Universitat Rovira i Virgili
    Any de publicació de la revista: 2023
    Tipus de publicació: Journal Publications
  • Paraules clau:

    Artificial Intelligence,Computer Science Applications,Computer Science, Artificial Intelligence,Engineering (Miscellaneous),Engineering, Electrical & Electronic,Operations Research & Management Science
    Travelling salesman problem
    Statistical disclosure control
    Microaggregation
    K-anonymity
    Data-oriented microaggregation
    Data protection
    Data privacy
    Algorithm
    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
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