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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CreationDate 2018-02-07 11:35
Creator Pappalardo Luca, lucapappalardo1984@gmail.com, orcid.org/0000-0002-1547-6007
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Field/Scope of use Non-commercial only
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Owner Pappalardo Luca, lucapappalardo1984@gmail.com, orcid.org/0000-0002-1547-6007
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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.
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Territory of use World Wide
ThematicCluster Human Mobility Analytics
UsageMode as-a-Service by SoBigData Infrastructure
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system:type SoBigData.eu: Method
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Author Pappalardo Luca
Maintainer Pappalardo Luca
Version 1
Last Updated 26 September 2019, 12:27 (CEST)
Created 26 September 2019, 12:27 (CEST)