Articles producció científica> Enginyeria Informàtica i Matemàtiques

Microaggregation- and permutation-based anonymization of movement data

  • Datos identificativos

    Identificador: imarina:3665478
    Autores:
    Domingo-Ferrer, JosepTrujillo-Rasua, Rolando
    Resumen:
    Movement data, that is, trajectories of mobile objects, are automatically collected in huge quantities by technologies such as GPS, GSM or RFID, among others. Publishing and exploiting such data is essential to improve transportation, to understand the dynamics of the economy in a region, etc. However, there are obvious threats to the privacy of individuals if their trajectories are published in a way which allows re-identification of the individual behind a trajectory. We contribute to the literature on privacy-preserving publication of trajectories by presenting a distance measure for trajectories which naturally considers both spatial and temporal aspects of trajectories, is computable in polynomial time, and can cluster trajectories not defined over the same time span. Our distance measure can be naturally instantiated using other existing similarity measures for trajectories that are appropriate for anonymization purposes. Then, we propose two heuristics for trajectory anonymization which yield anonymized trajectories formed by fully accurate true original locations. The first heuristic is based on trajectory microaggregation using the above distance and on location permutation; it effectively achieves trajectory k-anonymity. The second heuristic is based only on location permutation; it gives up trajectory k-anonymity and aims at location k-diversity. The strong point of the second heuristic is that it takes into account reachability constraints when computing anonymized trajectories. Experimental results on a synthetic data set and a real-life data set are presented; for similar privacy protection levels and most reasonable parameter choices, our two methods offer better utility than comparable previous proposals in the literature.
  • Otros:

    Autor según el artículo: Domingo-Ferrer, Josep; Trujillo-Rasua, Rolando
    Departamento: Enginyeria Informàtica i Matemàtiques
    Autor/es de la URV: Domingo Ferrer, Josep / Trujillo Rasua, Rolando
    Palabras clave: Trajectory Permutation Movement data Microaggregation Data privacy Anonymization
    Resumen: Movement data, that is, trajectories of mobile objects, are automatically collected in huge quantities by technologies such as GPS, GSM or RFID, among others. Publishing and exploiting such data is essential to improve transportation, to understand the dynamics of the economy in a region, etc. However, there are obvious threats to the privacy of individuals if their trajectories are published in a way which allows re-identification of the individual behind a trajectory. We contribute to the literature on privacy-preserving publication of trajectories by presenting a distance measure for trajectories which naturally considers both spatial and temporal aspects of trajectories, is computable in polynomial time, and can cluster trajectories not defined over the same time span. Our distance measure can be naturally instantiated using other existing similarity measures for trajectories that are appropriate for anonymization purposes. Then, we propose two heuristics for trajectory anonymization which yield anonymized trajectories formed by fully accurate true original locations. The first heuristic is based on trajectory microaggregation using the above distance and on location permutation; it effectively achieves trajectory k-anonymity. The second heuristic is based only on location permutation; it gives up trajectory k-anonymity and aims at location k-diversity. The strong point of the second heuristic is that it takes into account reachability constraints when computing anonymized trajectories. Experimental results on a synthetic data set and a real-life data set are presented; for similar privacy protection levels and most reasonable parameter choices, our two methods offer better utility than comparable previous proposals in the literature.
    Áreas temáticas: Theoretical computer science Software Medicina ii Matemática / probabilidade e estatística Interdisciplinar Information systems and management Ensino Engenharias iv Engenharias iii Engenharias i Control and systems engineering Comunicação e informação Computer science, information systems Computer science applications Ciencias sociales Ciências biológicas i Ciências ambientais Ciências agrárias i Ciência da computação Biodiversidade Astronomia / física Artificial intelligence 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: rolando.trujillo@urv.cat josep.domingo@urv.cat
    Identificador del autor: 0000-0002-8714-4626 0000-0001-7213-4962
    Fecha de alta del registro: 2024-10-12
    Versión del articulo depositado: info:eu-repo/semantics/acceptedVersion
    Enlace a la fuente original: https://www.sciencedirect.com/science/article/pii/S0020025512002794
    URL Documento de licencia: https://repositori.urv.cat/ca/proteccio-de-dades/
    Referencia al articulo segun fuente origial: Information Sciences. 208 55-80
    Referencia de l'ítem segons les normes APA: Domingo-Ferrer, Josep; Trujillo-Rasua, Rolando (2012). Microaggregation- and permutation-based anonymization of movement data. Information Sciences, 208(), 55-80. DOI: 10.1016/j.ins.2012.04.015
    DOI del artículo: 10.1016/j.ins.2012.04.015
    Entidad: Universitat Rovira i Virgili
    Año de publicación de la revista: 2012
    Tipo de publicación: Journal Publications
  • Palabras clave:

    Artificial Intelligence,Computer Science Applications,Computer Science, Information Systems,Control and Systems Engineering,Information Systems and Management,Software,Theoretical Computer Science
    Trajectory
    Permutation
    Movement data
    Microaggregation
    Data privacy
    Anonymization
    Theoretical computer science
    Software
    Medicina ii
    Matemática / probabilidade e estatística
    Interdisciplinar
    Information systems and management
    Ensino
    Engenharias iv
    Engenharias iii
    Engenharias i
    Control and systems engineering
    Comunicação e informação
    Computer science, information systems
    Computer science applications
    Ciencias sociales
    Ciências biológicas i
    Ciências ambientais
    Ciências agrárias i
    Ciência da computação
    Biodiversidade
    Astronomia / física
    Artificial intelligence
    Administração pública e de empresas, ciências contábeis e turismo
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