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Human Mobility Data Privacy Risk Estimator

This method is a fast and flexible approach to estimate privacy risk in human mobility data. The idea is to train classifiers to capture the relation between individual mobility patterns and the level of privacy risk of individuals. We show the effectiveness of our approach by an extensive experiment on real-world GPS data in two urban areas and investigate the relations between human mobility patterns and the privacy risk of individuals.

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Field Value
Accessibility Both
AccessibilityMode Download
Availability On-Site
Basic rights Download
CreationDate 2018-02-07 11:35
Creator Pappalardo, Luca, lucapappalardo1984@gmail.com, orcid.org/0000-0002-1547-6007
Field/Scope of use Non-commercial only
Group Sustainable Cities for Citizens
Owner Pappalardo, Luca, lucapappalardo1984@gmail.com, orcid.org/0000-0002-1547-6007
RelatedPaper R. Pellungrini, L. Pappalardo, F. Pratesi, A. Monreale. A data mining approach to estimate privacy risk in human mobility data. ACM Transactions on Intelligent Systems and Technology (TIST), 9(3), pp. 31:1–31:27.
Sublicense rights No
Territory of use World Wide
Thematic Cluster Human Mobility Analytics [HMA]
UsageMode as-a-Service by SoBigData Infrastructure
system:type Method
Management Info
Field Value
Author Pappalardo Luca
Maintainer Pappalardo Luca
Version 1
Last Updated 8 September 2023, 12:13 (CEST)
Created 29 June 2018, 11:34 (CEST)