Abstract
The massive deployment of low-end wireless Internet of things (IoT)
devices opens the challenge of finding de-centralized and lightweight
alternatives for secret key distribution. A possible solution, coming
from the physical layer, is the secret key generation (SKG) from channel
state information (CSI) during the channel’s coherence time. This work
acknowledges the fact that the CSI consists of deterministic
(predictable) and stochastic (unpredictable) components, loosely
captured through the terms large-scale and small-scale fading,
espectively. Hence, keys must be generated using only the random and
unpredictable part. To detrend CSI measurements from deterministic
components, a simple and lightweight approach based on Kalman filters is
proposed and is evaluated using an implementation of the complete SKG
protocol (including privacy amplification that is typically missing in
many published works). In our study we use a massive multiple input
multiple output (mMIMO) orthogonal frequency division multiplexing
outdoor measured CSI dataset. The threat model assumes a passive
eavesdropper in the vicinity (at 1 meter distance or less) from one of
the legitimate nodes and the Kalman filter is parameterized to maximize
the achievable key rate.