Practical Privacy-Preserving Indoor Localization Based on Secure Two-Party Computation

We present a privacy-preserving indoor localization scheme based on received signal strength measurements, e.g., from WiFi access points. Our scheme preserves the privacy of both the client's location and the service provider's database by using secure two-party computation instantiated with known cryptographic primitives, namely, Paillier encryption and garbled circuits. We describe a number of optimizations that reduce the computation and communication overheads of the scheme and provide theoretical evaluations of these overheads. We also demonstrate the feasibility of the scheme by developing a proof-of-concept implementation for Android smartphones and commodity servers. This implementation allows us to validate the practical performance of our scheme and to show that it is feasible for practical use in certain types of indoor localization applications.

Automated summary

The proposed privacy-preserving indoor localization scheme uses received signal strength measurements from WiFi access points and secure two-party computation with cryptographic primitives to protect privacy. Optimizations reduce computation and communication overheads, and a proof-of-concept implementation on Android smartphones demonstrates practical feasibility for certain indoor localization applications.