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