Using Uncertainty to Provide Privacy-Preserving and High-Quality Location-Based Services

Location-based services, such as finding the nearest gas station, require users to supply their location information. However, a user’s location can be tracked without her consent or knowledge. Lowering the spatial and temporal resolution of location data sent to the server has been proposed as a solution. Although this technique is effective in protecting privacy, it may be overkill and the quality of desired services can be severely affected. In this paper, we investigate the relationship between uncertainty, privacy, and quality of services. We propose using probabilistic queries to precisely control location uncertainty. We also suggest a framework where uncertainty can be controlled to provide high quality, privacy-preserving services.