The new Casper: query processing for location services without compromising privacy
Mohamed F. Mokbel,Chi-Yin Chow,Walid G. Aref +2 more
- pp 763-774
TLDR
Zhang et al. as mentioned in this paper presented Casper1, a new framework in which mobile and stationary users can entertain location-based services without revealing their location information, which consists of two main components, the location anonymizer and the privacy-aware query processor.Abstract:
This paper tackles a major privacy concern in current location-based services where users have to continuously report their locations to the database server in order to obtain the service. For example, a user asking about the nearest gas station has to report her exact location. With untrusted servers, reporting the location information may lead to several privacy threats. In this paper, we present Casper1; a new framework in which mobile and stationary users can entertain location-based services without revealing their location information. Casper consists of two main components, the location anonymizer and the privacy-aware query processor. The location anonymizer blurs the users' exact location information into cloaked spatial regions based on user-specified privacy requirements. The privacy-aware query processor is embedded inside the location-based database server in order to deal with the cloaked spatial areas rather than the exact location information. Experimental results show that Casper achieves high quality location-based services while providing anonymity for both data and queries.read more
Citations
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Sparse Mobile Crowdsensing With Differential and Distortion Location Privacy
TL;DR: A novel location obfuscation mechanism combining differential privacy and distortion privacy, which reduces the data quality loss by up to 42% compared to the state-of-the-art methods with the same level of privacy protection.
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Cloaking locations for anonymous location based services: a hybrid approach
Chengyang Zhang,Yan Huang +1 more
TL;DR: A new hybrid framework called HiSC is proposed that balances the load between the AS and mobile clients and can elegantly balance the work load based on privacy requirements and client distribution, and provides close to optimal service quality.
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Dynamic path privacy protection framework for continuous query service over road networks
Imran Memon,Qasim Ali Arain +1 more
TL;DR: Simulation results show that Dynamic Path Privacy has better performances compared to some related region based algorithms such as IAPIT scheme, half symmetric lens based localization algorithm (HSL) and sequential approximate maximum a posteriori (AMAP) estimator scheme, but also provides better locatable ratio.
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Privacy-aware location data publishing
TL;DR: An O(Hn)-approximate algorithm under the local enlargement paradigm, where n is the maximum number of events a user could possibly cover and Hn is the Harmonic number of n, which guarantees that user locations are enlarged just enough to cover all events k times, and thus maximize the usefulness of the published data.
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Optimal Task Recommendation for Mobile Crowdsourcing With Privacy Control
TL;DR: In this paper, the authors identify fundamental tradeoffs among utility, privacy, and efficiency in mobile crowdsourcing and propose a flexible optimization framework that can be adjusted to any desired tradeoff point with joint efforts of MC platform and workers.
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