Physical-Layer Authentication of Commodity Wi-Fi Devices via Micro-Signals on CSI Curves

TL;DR

This paper introduces 'micro-CSI', a novel radio-frequency fingerprint derived from CSI micro-signals in commodity Wi-Fi devices, enabling highly accurate device authentication by exploiting hardware imperfections.

Contribution

The paper presents the discovery of micro-CSI as a new fingerprint, along with an extraction algorithm and a KNN-based authentication method for Wi-Fi device identification.

Findings

Micro-CSI is present in Wi-Fi 4/5/6 NICs due to hardware imperfections.

The extraction algorithm effectively isolates micro-CSI signals.

The authentication achieves over 99% attack detection with zero false alarms.

Abstract

This paper presents a new radiometric fingerprint that is revealed by micro-signals in the channel state information (CSI) curves extracted from commodity Wi-Fi devices. We refer to this new fingerprint as "micro-CSI". Our experiments show that micro-CSI is likely to be caused by imperfections in the radio-frequency circuitry and is present in Wi-Fi 4/5/6 network interface cards (NICs). We conducted further experiments to determine the most effective CSI collection configuration to stabilize micro-CSI. To extract micro-CSI from varying CSI curves, we developed a signal space-based extraction algorithm that effectively separates distortions caused by wireless channels and hardware imperfections under line-of-sight (LoS) scenarios. Finally, we implemented a micro-CSI-based device authentication algorithm that uses the k-Nearest Neighbors (KNN) method to identify 11 COTS Wi-Fi NICs from the same manufacturer in typical indoor environments. Our experimental results demonstrate that the micro-CSI-based authentication algorithm can achieve an average attack detection rate of over 99% with a false alarm rate of 0%.