research-article

An Optimization Framework for Active Physical-Layer Authentication

Authors:

Alex X. LiuAuthors Info & Claims

IEEE Transactions on Mobile Computing, Volume 23, Issue 1

Pages 164 - 179

https://doi.org/10.1109/TMC.2022.3217055

Published: 01 January 2024 Publication History

Abstract

This paper concerns the problem of the parameter optimization of an active Physical-Layer Authentication (PLA) scheme, which is crucial for minimizing the distortion on the base signal carrying the original message caused by embedding a tag. An inappropriate parameter may significantly lower the efficiency of the entire period of message transmission. In this paper, we propose an optimization framework for an active PLA scheme and further propose a new systematic metric, defined as Secure Authentication Efficiency (SAE). In the proposed framework, we minimize the aforementioned distortion by tuning three parameters, i.e., the Probability of Message Transmission (PMT), the Probability of Message Outage (PMO), and the Probability of Secure Authentication (PSA). The proposed optimization framework deepens the understanding of the correlation between the parameters of an active PLA scheme and the conditions of a wireless channel, and allows us to systematically optimize the parameters of the active PLA scheme. Then, we establish an objective function by maximizing the SAE with both PMT and PMO constraints. We implement our approach and conduct extensive performance comparisons. Our experimental results show that when the SNR at the receiver is more than 15 dB, our approach achieves an average SAE of greater than 80%, whereas the prior scheme without parameter optimization degenerates to zero SAE under some conditions, e.g., high SNR at adversary or high communication rate.

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Cited By

Huang JLiu BMiao CZhang XLiu JSu LLiu ZGu Y(2023)PhyFinAtt: An Undetectable Attack Framework Against PHY Layer Fingerprint-Based WiFi AuthenticationIEEE Transactions on Mobile Computing10.1109/TMC.2023.333895423:7(7753-7770)Online publication date: 4-Dec-2023
https://dl.acm.org/doi/10.1109/TMC.2023.3338954
Duan ZChang ZXie NSun WNiyato D(undefined)Adaptive Strategies in Enhancing Physical Layer Security: A Comprehensive SurveyACM Computing Surveys10.1145/3715319
https://dl.acm.org/doi/10.1145/3715319

Index Terms

An Optimization Framework for Active Physical-Layer Authentication
1. Networks
  1. Network types
    1. Mobile networks
    2. Wireless access networks
2. Security and privacy
  1. Cryptography
  2. Security services

Index terms have been assigned to the content through auto-classification.

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cover image IEEE Transactions on Mobile Computing

IEEE Transactions on Mobile Computing Volume 23, Issue 1

Jan. 2024

1000 pages

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1536-1233 © 2022 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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IEEE Educational Activities Department

United States

Publication History

Published: 01 January 2024

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Cited By

Huang JLiu BMiao CZhang XLiu JSu LLiu ZGu Y(2023)PhyFinAtt: An Undetectable Attack Framework Against PHY Layer Fingerprint-Based WiFi AuthenticationIEEE Transactions on Mobile Computing10.1109/TMC.2023.333895423:7(7753-7770)Online publication date: 4-Dec-2023
https://dl.acm.org/doi/10.1109/TMC.2023.3338954
Duan ZChang ZXie NSun WNiyato D(undefined)Adaptive Strategies in Enhancing Physical Layer Security: A Comprehensive SurveyACM Computing Surveys10.1145/3715319
https://dl.acm.org/doi/10.1145/3715319

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