基于卡尔曼滤波去趋势的物理层密钥生成
Physical Layer Secret Key Generation with Kalman Filter Detrending
AI总结：
针对物联网设备密钥分发挑战，提出基于卡尔曼滤波的轻量级CSI去趋势方法，利用完整SKG协议在mMIMO室外数据集上验证，有效提升可实现密钥速率并抵御近距离窃听者。
摘要：
低端无线物联网设备的广泛部署带来了寻找去中心化和轻量级密钥分发替代方案的挑战。来自物理层的一种可能解决方案是在信道相干时间内利用信道状态信息（CSI）生成密钥（SKG）。本研究认识到CSI由确定性（可预测）和随机性（不可预测）成分组成，分别通过大尺度和小尺度衰落这两个术语来粗略描述。因此，必须仅使用随机且不可预测的部分来生成密钥。为了从CSI测量中去除确定性成分，提出了一种基于卡尔曼滤波器的简单轻量级方法，并使用完整的SKG协议实现（包括许多已发表工作中通常缺失的隐私放大）进行了评估。在我们的研究中，我们使用了一个大规模多输入多输出正交频分复用室外测量CSI数据集。威胁模型假设被动窃听者位于距离合法节点1米或更近的位置，并且卡尔曼滤波器经过参数化以最大化可实现密钥速率。
英文摘要：
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, respectively. 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.
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