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

arXiv: https://arxiv.org/abs/2308.00373 · HTML: https://mlsanity.com/paper/2308.00373/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 1 Aug 2023.

## Built on by (most cited first, 1 of 1)

- [Exploiting Radio Frequency Fingerprints for Device Identification: Tackling Cross-receiver Challenges in the Source-data-free Scenario](https://mlsanity.com/paper/2512.16648/) (2025)

## Abstract (arXiv)

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%.