research-article

Artificial Noise-Aided MIMO Physical Layer Authentication With Imperfect CSI

Authors:

Jake Bailey Perazzone,

Brian M. Sadler,

Rick S. BlumAuthors Info & Claims

IEEE Transactions on Information Forensics and Security, Volume 16

Pages 2173 - 2185

https://doi.org/10.1109/TIFS.2021.3050599

Published: 01 January 2021 Publication History

Abstract

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.

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Cited By

Tan HXie NLiu A(2024)An Optimization Framework for Active Physical-Layer AuthenticationIEEE Transactions on Mobile Computing10.1109/TMC.2022.321705523:1(164-179)Online publication date: 1-Jan-2024
https://dl.acm.org/doi/10.1109/TMC.2022.3217055
Kong ZSong JYang SGan LMeng WHuang TChen S(2024)Distributed Robust Artificial-Noise-Aided Secure Precoding for Wiretap MIMO Interference ChannelsIEEE Transactions on Information Forensics and Security10.1109/TIFS.2024.348654819(10130-10140)Online publication date: 1-Jan-2024
https://dl.acm.org/doi/10.1109/TIFS.2024.3486548
Jing THuang HGao QWu YHuo YWang Y(2024)Multi-User Physical Layer Authentication Based on CSI Using ResNet in Mobile IIoTIEEE Transactions on Information Forensics and Security10.1109/TIFS.2023.334009019(1896-1907)Online publication date: 1-Jan-2024
https://dl.acm.org/doi/10.1109/TIFS.2023.3340090
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cover image IEEE Transactions on Information Forensics and Security

IEEE Transactions on Information Forensics and Security Volume 16, Issue

2021

1912 pages

ISSN:1556-6013

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1556-6021 © 2021 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See https://www.ieee.org/publications/rights/index.html for more information.

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Published: 01 January 2021

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Cited By

Tan HXie NLiu A(2024)An Optimization Framework for Active Physical-Layer AuthenticationIEEE Transactions on Mobile Computing10.1109/TMC.2022.321705523:1(164-179)Online publication date: 1-Jan-2024
https://dl.acm.org/doi/10.1109/TMC.2022.3217055
Kong ZSong JYang SGan LMeng WHuang TChen S(2024)Distributed Robust Artificial-Noise-Aided Secure Precoding for Wiretap MIMO Interference ChannelsIEEE Transactions on Information Forensics and Security10.1109/TIFS.2024.348654819(10130-10140)Online publication date: 1-Jan-2024
https://dl.acm.org/doi/10.1109/TIFS.2024.3486548
Jing THuang HGao QWu YHuo YWang Y(2024)Multi-User Physical Layer Authentication Based on CSI Using ResNet in Mobile IIoTIEEE Transactions on Information Forensics and Security10.1109/TIFS.2023.334009019(1896-1907)Online publication date: 1-Jan-2024
https://dl.acm.org/doi/10.1109/TIFS.2023.3340090
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Li XFeng CSong FJiang CZhang YLi KZhang XChen X(2022)ProtegoProceedings of the 28th Annual International Conference on Mobile Computing And Networking10.1145/3495243.3560547(55-68)Online publication date: 14-Oct-2022
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