With the increasing popularity of the Internet of Things (IoT), device identification and authentication has become a critical security issue. Recently, Radio Frequency (RF) fingerprint-based identification schemes have attracted wide attention as they extract the inherent characteristics of hardware circuits which is very hard to forge.
In this research project, we aim to:
- Established an very large, properly pre-processed dataset of radio signal frames from 43 different WIFI module. Such huge dataset seems has never showed up in other research.
- Try to propose several useful machine learning model to extract features from analog radio signal. Sufficient experiment should be implemented for comparison about F1-score, robustness to noise, model size&FLOPs
