Demonstration of Indoor Location Privacy Enforcement using Obfuscation^⁎

We apply discrete-event-control-theoretic techniques for opacity enforcement by insertion or deletion of output events to the problem of location privacy enforcement in an indoor environment where users are continuously monitored by IoT devices. We design an obfuscator of user trajectories in a grid model with obstacles. The obfuscator must preserve a secret (e.g., visits to secret cells of the grid), while at the same time enforce feasibility and utility constraints for obfuscated trajectories. We implement the obfuscator to map the true location of the user to an obfuscated location, in real time, using services provided by a data server called the Global Data Plane which records sensor readings from IoT devices and publishes them to subscribers. We explain how scalability of obfuscator synthesis (off-line) and instantiation (online) is achieved. We demonstrate the approach on a grid with over 1,500 cells modeling the first floor of a university building, where location estimation is achieved using the ALPS Acoustic Location Processing System.