Articles producció científica> Enginyeria Informàtica i Matemàtiques

Microaggregation- and permutation-based anonymization of movement data

  • Dades identificatives

    Identificador: imarina:3665478
    Autors:
    Domingo-Ferrer, JosepTrujillo-Rasua, Rolando
    Resum:
    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.
  • Altres:

    Autor segons l'article: Domingo-Ferrer, Josep; Trujillo-Rasua, Rolando
    Departament: Enginyeria Informàtica i Matemàtiques
    Autor/s de la URV: Domingo Ferrer, Josep / Trujillo Rasua, Rolando
    Paraules clau: Trajectory Permutation Movement data Microaggregation Data privacy Anonymization
    Resum: 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.
    Àrees temàtiques: 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
    Accès a la llicència d'ús: https://creativecommons.org/licenses/by/3.0/es/
    Adreça de correu electrònic de l'autor: rolando.trujillo@urv.cat josep.domingo@urv.cat
    Identificador de l'autor: 0000-0002-8714-4626 0000-0001-7213-4962
    Data d'alta del registre: 2024-10-12
    Versió de l'article dipositat: info:eu-repo/semantics/acceptedVersion
    Enllaç font original: https://www.sciencedirect.com/science/article/pii/S0020025512002794
    URL Document de llicència: https://repositori.urv.cat/ca/proteccio-de-dades/
    Referència a l'article segons font original: Information Sciences. 208 55-80
    Referència 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 de l'article: 10.1016/j.ins.2012.04.015
    Entitat: Universitat Rovira i Virgili
    Any de publicació de la revista: 2012
    Tipus de publicació: Journal Publications
  • Paraules clau:

    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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