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基于 RIS 的抗 DoS 攻击安全车载通信中密钥生成

RIS-Enabled Secret Key Generation for Secured Vehicular Communication in the Presence of Denial-of-Service Attacks.

机构信息

James Watt School of Engineering, University of Glasgow, Glasgow G12 8QQ, UK.

Department of Communications Engineering, Military Technical College, Cairo 11646, Egypt.

出版信息

Sensors (Basel). 2023 Apr 19;23(8):4104. doi: 10.3390/s23084104.

DOI:10.3390/s23084104
PMID:37112445
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10146868/
Abstract

Wireless communication has become an integral part of modern vehicles. However, securing the information exchanged between interconnected terminals poses a significant challenge. Effective security solutions should be computationally inexpensive, ultra-reliable, and capable of operating in any wireless propagation environment. Physical layer secret key generation has emerged as a promising technique, which leverages the inherent randomness of wireless-channel responses in amplitude and phase to generate high-entropy symmetric shared keys. The sensitivity of the channel-phase responses to the distance between network terminals makes this technique a viable solution for secure vehicular communication, given the dynamic behavior of these terminals. However, the practical implementation of this technique in vehicular communication is hindered by fluctuations in the communication link between line-of-sight (LoS) and non-line-of-sight (NLoS) conditions. This study introduces a key-generation approach that uses a reconfigurable intelligent surface (RIS) to secure message exchange in vehicular communication. The RIS improves the performance of key extraction in scenarios with low signal-to-noise ratios (SNRs) and NLoS conditions. Additionally, it enhances the network's security against denial-of-service (DoS) attacks. In this context, we propose an efficient RIS configuration optimization technique that reinforces the signals received from legitimate users and weakens the signals from potential adversaries. The effectiveness of the proposed scheme is evaluated through practical implementation using a 1-bit RIS with 64×64 elements and software-defined radios operating within the 5G frequency band. The results demonstrate improved key-extraction performance and increased resistance to DoS attacks. The hardware implementation of the proposed approach further validated its effectiveness in enhancing key-extraction performance in terms of the key generation and mismatch rates, while reducing the effect of the DoS attacks on the network.

摘要

无线通信已经成为现代车辆不可或缺的一部分。然而,保护相互连接的终端之间交换的信息是一个重大挑战。有效的安全解决方案应该具有计算成本低、超可靠和能够在任何无线传播环境中运行的特点。物理层密钥生成已成为一种很有前途的技术,它利用无线信道响应的幅度和相位的固有随机性来生成高熵对称共享密钥。由于网络终端的动态行为,信道相位响应对网络终端之间距离的敏感性使得该技术成为安全车辆通信的可行解决方案。然而,由于视距 (LoS) 和非视距 (NLoS) 条件下通信链路的波动,该技术在车辆通信中的实际实现受到阻碍。本研究提出了一种使用可重构智能表面 (RIS) 来确保车辆通信中消息交换的密钥生成方法。RIS 提高了低信噪比 (SNR) 和 NLoS 条件下的密钥提取性能。此外,它增强了网络对拒绝服务 (DoS) 攻击的安全性。在这种情况下,我们提出了一种有效的 RIS 配置优化技术,该技术可以增强从合法用户接收的信号,并削弱来自潜在对手的信号。通过使用具有 64×64 个元素的 1 位 RIS 和在 5G 频段内运行的软件定义无线电进行实际实现,评估了所提出方案的有效性。结果表明,该方案提高了密钥提取性能,并提高了对 DoS 攻击的抵抗力。该方法的硬件实现进一步验证了其在提高密钥提取性能、降低密钥生成和失配率以及减少 DoS 攻击对网络影响方面的有效性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4bd/10146868/7f67a6116ad9/sensors-23-04104-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4bd/10146868/9f23a91242ef/sensors-23-04104-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4bd/10146868/cb095e547b5b/sensors-23-04104-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4bd/10146868/023561fea03e/sensors-23-04104-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4bd/10146868/090ac8f4bb6c/sensors-23-04104-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4bd/10146868/1035d0f4bd66/sensors-23-04104-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4bd/10146868/f5b88395becd/sensors-23-04104-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4bd/10146868/7f67a6116ad9/sensors-23-04104-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4bd/10146868/9f23a91242ef/sensors-23-04104-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4bd/10146868/cb095e547b5b/sensors-23-04104-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4bd/10146868/023561fea03e/sensors-23-04104-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4bd/10146868/090ac8f4bb6c/sensors-23-04104-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4bd/10146868/1035d0f4bd66/sensors-23-04104-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4bd/10146868/f5b88395becd/sensors-23-04104-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4bd/10146868/7f67a6116ad9/sensors-23-04104-g007.jpg

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本文引用的文献

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Intelligent Reflecting Surface-Assisted Physical Layer Key Generation with Deep Learning in MIMO Systems.基于深度学习的 MIMO 系统中智能反射面辅助物理层密钥生成。
Sensors (Basel). 2022 Dec 21;23(1):55. doi: 10.3390/s23010055.
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SE-CPPA: A Secure and Efficient Conditional Privacy-Preserving Authentication Scheme in Vehicular Ad-Hoc Networks.SE-CPPA:一种车载自组织网络中安全高效的条件隐私保护认证方案。
Sensors (Basel). 2021 Dec 8;21(24):8206. doi: 10.3390/s21248206.
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Blockchain-Based Authentication in Internet of Vehicles: A Survey.
基于区块链的车辆互联网认证:一项综述。
Sensors (Basel). 2021 Nov 27;21(23):7927. doi: 10.3390/s21237927.
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A Survey of Security Services, Attacks, and Applications for Vehicular Ad Hoc Networks (VANETs).车载自组织网络(VANETs)的安全服务、攻击及应用综述
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