Physical Layer Secret Key Generation Leveraging Proactive Pilot Contamination

Physical layer-based secret key generation has garnered significant attention due to its inherent advantages of lightweight implementation, information-theoretic security, and broad applicability for mobile devices. The reciprocal randomness of the wireless channel ensures the consistent generation of secret bits between two communicating parties. However, it also suffers from the degradation of the efficiency of key generation attributed to the adverse impact of ambient noise, despite sustained efforts to mitigate the inconsistency during quantization. We find that a slight perturbation of the pilot signal, without affecting the correct reception of data frames, induces a corresponding change in the channel response, making it possibly adaptable to the target quantization strategies, thereby reducing the probability of key mismatch. Therefore, we take a different viewpoint on proactive contamination of the pilot signals to obtain the desired channel measurements for accurate physical layer secret key generation. Specifically, we design an adaptive pilot manipulation to avoid the expected channel measurements being too close to the quantization thresholds, enabling high quantization consistency. Furthermore, we also develop a random cross-threshold mechanism to prevent attackers from inferring the quantization results by monitoring the trend of pilot signal variations. A reliable long training sequence (LTS) modification mechanism is incorporated into our method to ensure communication performance by adaptively adjusting the scale of the pilot signal. To validate the effectiveness of our proposed method, we implement a prototype by re-configuring software modules in GNU radio running on the USRP platform. Extensive experiments demonstrate that our scheme outperforms existing representative quantization schemes with better key generation performance.