WiFi Interference-Based Adversarial Attacks on NTC Using CSI Sensing

With the emergence of next generation networks, Network Traffic Classification (NTC) has seen greater importance in network management and security. Recently, Channel State Information (CSI) based WiFi sensing techniques have shown their potential for NTC applications [1], [2] as a privacy-preserving yet effective tool. As CSI could be prone to interference, this paper examines the performance of CSI-based NTC models under interference-induced adversarial attacks. Specifically, the impact of spectral allocation of the interference, underlying interfering network traffic type, and physical location of the interference are studied and quantified. We conducted experiments using off-the-shelf devices to test the NTC performance, with and without the adversarial interference attack of ping, buffered video streaming, and live video streaming network traffics. Subsequently, we found that spectral allocation of the attacking interference and the underlying traffic types of interference could be used to deceive the established NTC model, and different network traffic types show different robustness across the interference cases. Namely, ping suffers the most in the spectrally manipulated attack, with the classification accuracy down to as low as 23.2%, whereas Twitch might be completely misidentified as other traffic in underlying traffic type controlled attack.