Vehicular mobility traces are datasets of vehicle location records in a region with high spatio-temporal precision. The access to this sensitive information can threaten the safety and privacy of drivers, given that the analysis of this data makes it possible to discover other contextual and latent information, such as daily home routes or workplace's address. To prevent this, many obfuscation and anonymization techniques have been proposed to mitigate the problem of user location privacy. In this work, we analyze an anonymization technique called mix-zone, which selects urban regions that promote the simultaneous anonymization of vehicles by changing their current pseudonym. We show how information about drivers' behavior in a city, such as their road preferences, can be used to reidentify their trajectories. To do this, we present a simple and efficient re-identification technique that uses only two georeferenced points as input data. We validate our technique with a real dataset of taxicabs, being able to re-identify up to 100% of the anonymized trajectories.
Give Me Two Points and I'll Tell You Who You Are
2019 IEEE Intelligent Vehicles Symposium (IV) ; 1081-1087
2019-06-01
348963 byte
Conference paper
Electronic Resource
English
Online Contents | 1996
|Transportation Research Record | 2007
|Acceptable Risk Level - I'll give you the statistics...
Online Contents | 2004
I'll Tell You What I Think! A National Review of How the Public Perceives Pricing
Online Contents | 2007
|Give me the chance and I'll show you - Four design students, four great Focus ideas
Online Contents | 2004