AnonyCast: privacy-preserving location distribution for anonymous crowd tracking systems

Fusion of infrastructure-based pedestrian tracking systems and embedded sensors on mobile devices holds promise for providing accurate positioning in large public buildings. However, privacy concerns regarding handling of sensitive user location data potentially disrupt the adoption of such systems. This paper presents AnonyCast, a novel privacy-aware mechanism for delivering precise location information measured by crowd-tracking systems to individual pedestrians' smartphones. AnonyCast uses sparsely placed Bluetooth Low Energy transmitters to advertise location-dependent, time-varying keys. Using location measurements, AnonyCast estimates a subset of keys that each pedestrian's phone receives along its path. By combining a cryptography scheme called CP-ABE with a novel greedy algorithm for key selection, it encrypts each path before publishing, allowing users to decrypt only their own trajectories. The results from field experiments show that AnonyCast delivers accurate locations over 84% of time, bounding probability of unauthorized access to one's location below 1%.

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