Wi-Fi RFFI Protocol-Level Emulated Traces

This resource provides protocol-level emulated Wi-Fi 802.11 signal traces with hardware impairments, designed for RFFI-based impersonation detection research.

Overview

The dataset supports the study of radio frequency fingerprinting identification (RFFI) for detecting device impersonation in Wi-Fi networks. Signals are emulated using GNU Radio with device-specific hardware impairments including CFO and IQ imbalance, along with basic channel effects. Each legitimate device has a unique hardware fingerprint, while attacker devices share the MAC address of their target legitimate device while retaining distinct hardware characteristics.

What is included

  • IQ traces for 4 legitimate devices
  • IQ traces for 4 attacker devices, each impersonating a corresponding legitimate device
  • hardware impairments: CFO and IQ imbalance
  • channel effects: basic propagation simulation via GNU Radio
  • scripts/analyze.py for feature extraction and XGBoost-based device classification

Dataset context

Each .npy file contains complex64 IQ samples with a packet length of 3840 samples. The dataset was generated to evaluate unsupervised anomaly detection for Wi-Fi impersonation attacks at the protocol level, complementing the signal-level synthetic dataset.

File Type Packets
legitimate_device_01.npy Legitimate 7919
legitimate_device_02.npy Legitimate 8299
legitimate_device_03.npy Legitimate 7595
legitimate_device_04.npy Legitimate 8854
attacker_device_05_impersonates_01.npy Attacker 1351
attacker_device_06_impersonates_02.npy Attacker 1167
attacker_device_07_impersonates_03.npy Attacker 1630
attacker_device_08_impersonates_04.npy Attacker 1999

Why it matters

This dataset offers a reproducible setting for evaluating RFFI-based anomaly detection under protocol-level emulation, providing a more realistic benchmark than purely synthetic signal-level data.

Access

Example result

Confusion matrix preview

This preview shows the XGBoost classification confusion matrix on the protocol-level emulated dataset, illustrating the separability of device-specific RF fingerprints across legitimate and attacker devices.

Citation

If you use this resource, please cite the related publication above.