An Experimental Study of CSI Management to Preserve Location Privacy

Abstract

Passive device-free localization of a person exploiting the Channel State Information (CSI) from Wi-Fi signals is quickly becoming a reality. While this capability would enable new applications and services, it also raises concerns about citizens' privacy. In this work, we propose a carefully-crafted obfuscating technique against one of such CSI-based localization methods. In particular, we modify the transmitted I/Q samples by leveraging an irreversible randomized sequence. I/Q symbol manipulation at the transmitter distorts the location-specific information in the CSI while preserving communication, so that an attacker can no longer derive information on user's location. We test this technique against a Neural Network (NN)-based localization system and show that the randomization of the CSI makes undesired localization practically unfeasible. Both the localization system and the randomization CSI management are implemented in real devices. The experimental results obtained in our laboratory show that the considered localization method (first proposed in an MSc thesis) works smoothly regardless of the environment, and that adding random information to the CSI mess up the localization, thus providing the community with a system that preserve location privacy and communication performance at the same time.