Visible light communication (VLC) is a promising technology with a high data rate that can supplement radio frequency communication. Although VLC systems have a natural advantage of high security due to the line-of-sight light propagation characteristic, they are still vulnerable when facing an open environment. Device fingerprinting is a technique that is widely viewed to detect transmitter impersonation attack in radio frequency (RF) based wireless systems. In this paper, we introduce the fingerprinting technique to discriminate illegal transmitting devices in VLC systems. We first investigate the hardware imperfections of the VLC transmitter, which can provide a unique device ID. Then we implement a feature separation network for transmitter fingerprinting (TF-FSN) and design a two-stage training strategy to obtain a stable classifier. Finally, we experimentally demonstrate the feasibility and performance of the proposed method. The results show that the accuracy of identification and verification is 92.65% and 98%, respectively. Moreover, our method is robust over different distances and a wide range of signal-to-noise ratios.

中文翻译：

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通过深度特征分离网络对 VLC 系统进行发射机指纹识别


可见光通信（VLC）是一种很有前途的技术，具有高数据速率，可以补充射频通信。尽管VLC系统由于视距光传播特性而具有高安全性的天然优势，但在面对开放环境时仍然容易受到攻击。设备指纹识别是一种被广泛认为用于检测基于射频 (RF) 的无线系统中的发射器假冒攻击的技术。在本文中，我们介绍了识别 VLC 系统中非法传输设备的指纹技术。我们首先调查VLC发射器的硬件缺陷，它可以提供唯一的设备ID。然后，我们实现了用于发射机指纹识别的特征分离网络（TF-FSN），并设计了两阶段训练策略以获得稳定的分类器。最后，我们通过实验证明了该方法的可行性和性能。结果表明，识别准确率达92.65%，验证准确率达98%。此外，我们的方法在不同的距离和广泛的信噪比范围内都具有鲁棒性。