LocLok: location cloaking with differential privacy via hidden markov model. We demonstrate LocLok, a LOCation-cLOaKing system to protect the locations of a user with differential privacy. LocLok has two features: (a) it protects locations under temporal correlations described through hidden Markov model; (b) it releases the optimal noisy location with the planar isotropic mechanism (PIM), the first mechanism that achieves the lower bound of differential privacy. We show the detailed computation of LocLok with the following components: (a) how to generate the possible locations with Markov model, (b) how to perturb the location with PIM, and (c) how to make inference about the true location in Markov model. An online system with real-word dataset will be presented with the computation details.
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References in zbMATH (referenced in 2 articles )
Showing results 1 to 2 of 2.
- Bavendiek, Kai; Schupp, Sibylle: A process calculus for privacy-preserving protocols in location-based service systems (2022)
- Awan, Jordan; Slavković, Aleksandra: Structure and sensitivity in differential privacy: comparing (K)-norm mechanisms (2021)