Artificial Noise-Aided MIMO Physical Layer Authentication With Imperfect CSI
Artificial Noise-Aided MIMO Physical Layer Authentication With Imperfect CSI
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DOI：
10.1109/tifs.2021.3050599
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发表时间：
2021-01-01
影响因子：
6.8
通讯作者：
Blum, Rick S.
中科院分区：
文献类型：
--
作者：
Perazzone, Jake Bailey;Yu, Paul L.;Blum, Rick S.
在物理层嵌入指纹是一种高度可调的无线通信认证框架，它通过在噪声中隐藏传统的HMAC标签来实现信息论安全。在多天线的情况下，可以传输人工噪声(AN)来进一步遮蔽标签。然而，AN策略依赖于对合法用户之间的信道状态信息(CSI)的完美了解。当CSI不完全知道时，增加的噪声会泄漏到接收器的观测中。在这篇文章中，我们探索在只有在发送方和接收方可用的不完美的CSI的情况下，AN是否仍然提高了指纹嵌入认证框架的安全性。具体地说，我们讨论和设计了用于解释泄漏的检测器，并分析了对手从观察到的传输中恢复密钥的能力。我们比较了最佳完美CSI检测器与非完美CSI稳健匹配滤波测试和广义似然比测试(GLRT)的检测和安全性能。我们发现，利用AN可以极大地提高安全性，但当CSI知识质量较差时，会受到收益递减的影响。事实上，我们发现，在某些情况下，向AN分配额外的功率可能会开始降低密钥安全性。
Fingerprint embedding at the physical layer is a highly tunable authentication framework for wireless communication that achieves information-theoretic security by hiding a traditional HMAC tag in noise. In a multiantenna scenario, artificial noise (AN) can be transmitted to obscure the tag even further. The AN strategy, however, relies on perfect knowledge of the channel state information (CSI) between the legitimate users. When the CSI is not perfectly known, the added noise leaks into the receiver's observations. In this article, we explore whether AN still improves security in the fingerprint embedding authentication framework with only imperfect CSI available at the transmitter and receiver. Specifically, we discuss and design detectors that account for AN leakage and analyze the adversary's ability to recover the key from observed transmissions. We compare the detection and security performance of the optimal perfect CSI detector with the imperfect CSI robust matched filter test and a generalized likelihood ratio test (GLRT). We find that utilizing AN can greatly improve security, but suffers from diminishing returns when the quality of CSI knowledge is poor. In fact, we find that in some cases allocating additional power to AN can begin to decrease key security.