Passive Device-Free Multi-Point CSI Localization and Its Obfuscation with Randomized Filtering

Abstract

The use of Channel State Information (CSI) as a means of sensing the environment through Wi-Fi communications, and in particular to locate the position of unaware people, is moving from feasibility studies to high precision applications. The work we present in this paper explores how the use of multiple localization receivers can enhance the precision and robustness of device-free CSI-based localization with a method based on a state-of-the-art Convolutional Neural Network. Next we discuss how a randomized pre-filtering at the transmitter can hide the information that the CSI carries on the location of one person indoor formalizing the manipulation technique. Results are presented discussing two different ways of exploiting the multi-receiver redundancy and how, in any case, properly randomized pre-distortion at the transmitter can prevent localization even if the attack is carried out with multiple localization devices (receivers controlled by the attacker).