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通过瑞利背向散射进行光学系统识别。

Optical Systems Identification through Rayleigh Backscattering.

机构信息

Photonic Networks and Technologies Laboratory, National Inter-University Consortium for Telecommunications (CNIT), Via G. Moruzzi 1, 56124 Pisa, Italy.

TeCIP Institute, Scuola Superiore Sant'Anna, Via G. Moruzzi 1, 56124 Pisa, Italy.

出版信息

Sensors (Basel). 2023 Jun 1;23(11):5269. doi: 10.3390/s23115269.

Abstract

We introduce a technique to generate and read the digital signature of the networks, channels, and optical devices that possess the fiber-optic pigtails to enhance physical layer security (PLS). Attributing a signature to the networks or devices eases the identification and authentication of networks and systems thus reducing their vulnerability to physical and digital attacks. The signatures are generated using an optical physical unclonable function (OPUF). Considering that OPUFs are established as the most potent anti-counterfeiting tool, the created signatures are robust against malicious attacks such as tampering and cyber attacks. We investigate Rayleigh backscattering signal (RBS) as a strong OPUF to generate reliable signatures. Contrary to other OPUFs that must be fabricated, the RBS-based OPUF is an inherent feature of fibers and can be easily obtained using optical frequency domain reflectometry (OFDR). We evaluate the security of the generated signatures in terms of their robustness against prediction and cloning. We demonstrate the robustness of signatures against digital and physical attacks confirming the unpredictability and unclonability features of the generated signatures. We explore signature cyber security by considering the random structure of the produced signatures. To demonstrate signature reproducibility through repeated measurements, we simulate the signature of a system by adding a random Gaussian white noise to the signal. This model is proposed to address services including security, authentication, identification, and monitoring.

摘要

我们介绍了一种生成和读取具有光纤尾纤的网络、信道和光器件数字签名的技术,以增强物理层安全性(PLS)。为网络或设备分配签名可以简化网络和系统的识别和认证,从而降低它们受到物理和数字攻击的脆弱性。签名是使用光学物理不可克隆函数(OPUF)生成的。考虑到 OPUF 已被确立为最有效的防伪工具,因此创建的签名对篡改和网络攻击等恶意攻击具有很强的鲁棒性。我们研究了瑞利背向散射信号(RBS)作为一种强大的 OPUF 来生成可靠的签名。与必须制造的其他 OPUF 不同,基于 RBS 的 OPUF 是光纤的固有特征,可以使用光学频域反射计(OFDR)轻松获得。我们根据其对预测和克隆的鲁棒性来评估生成签名的安全性。我们证明了签名对数字和物理攻击的鲁棒性,证实了生成签名的不可预测性和不可克隆性。我们通过考虑生成签名的随机结构来探索签名的网络安全性。为了通过重复测量来演示签名的可重复性,我们通过向信号中添加随机高斯白噪声来模拟系统的签名。该模型旨在解决包括安全性、认证、识别和监控在内的服务。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7cd5/10256015/2570ca52e667/sensors-23-05269-g001.jpg

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