Privacy-Preserving Indoor Localisation and Navigation

Internet-based Indoor Navigation (IIN) services have recently received considerable attention, mainly because GPS technology is unavailable in indoor spaces and consumes considerable energy. On the other hand, predominant Smartphone OS localisation subsystems currently rely on server-side localisation processes, allowing the service provider to know the location of a user at all times. We have devised an innovative algorithm for protecting users from location tracking by the localisation service, without hindering the provision of fine-grained location updates on a continuous basis. Our proposed Temporal Vector Map (TVM) algorithm allows a user to accurately localise by exploiting a k-Anonymity Bloom (kAB) filter and a bestNeighbors generator of camouflaged localisation requests, both of which are shown to be resilient to a variety of privacy attacks.