Physical layer secret key generation using discrete wavelet packet transforme

Physical layer secret key generation leveraging reciprocity principle of the wireless channel is a promising substitute for traditional cryptography. However, in certain scenarios, the channel measurements extracted by the wireless transceivers are of high correlation but not similar. Therefore, preprocessing channel measurements prior to quantization is highly essential to facilitate successful generation of shared secret keys at the transceivers. In this paper, we put forth the idea of employing discrete wavelet packet transform (DWPT) for dynamic secret key generation in indoor environments. We propose two schemes which are employed at both the transceivers. Proposed method 1 (Prop. method-1) involves fixing the wavelet packet coefficients of selected terminal nodes in the wavelet packet tree to zero and proposed method 2 (Prop. method-2) involves compression of wavelet packet coefficients of selected terminal nodes. The performance of the proposed methods are evaluated using Pearson correlation coefficient, bit disagreement rate (BDR) and NIST randomness tests. Simulation results demonstrate that, Prop. method-1 performs well in terms of cross-correlation, especially when the measurement error variance is high. In contrast to Prop. method-1, Prop. method-2 renders better randomness at the expense of slightly reduced cross-correlation whilst both methods pass all eight NIST randomness tests. The tradeoff between cross-correlation and randomness can be improved owing to the richer signal analysis offered by DWPT. The simulation results are compared against existing works for validating performance of the proposed methods. Simulation results demonstrate that, DWPT based preprocessing is a highly promising solution for successful physical layer secret key generation.

Automated summary

This paper proposes a method for dynamic secret key generation in indoor environments using discrete wavelet packet transform (DWPT). Two schemes are introduced, with Prop. method-1 performing well under high measurement error variance and Prop. method-2 providing better randomness. Both methods pass NIST randomness tests and simulation results demonstrate the feasibility of DWPT.