Physical-Layer Authentication Using Channel State Information and Machine Learning

Germain, Ken St.; Kragh, Frank

doi:10.1109/icspcs50536.2020.9310070

Cited by 14 publications

(5 citation statements)

References 23 publications

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“…where h nm represents the channel from the mth transmit antenna to the nth receive antenna. H can be estimated from Y corresponding to the known reference signals (Schindler and Mellein, 2011;Germain et al, 2020). Y is used to obtain the data for SCC-SVM training and testing.…”

Section: System Modelmentioning

confidence: 99%

Secure authentication in MIMO systems: exploring physical limits

Abdrabou,

Gulliver

2024

Front. Comms. Net.

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Multiple-input multiple-output (MIMO) technology is employed to improve the reliability and capacity of wireless communication systems. However, the wireless communication environment creates vulnerabilities to spoofing attacks. Furthermore, the authentication challenges posed by the heterogeneous characteristics of wireless applications increase as diverse technologies facilitate the growing number of Internet of Things (IoT) devices. To address these challenges, adaptive physical-layer authentication (PLA) leveraging the inherent antenna diversity in MIMO systems is examined, and an information-theoretic perspective on PLA in MIMO systems is given. The real and imaginary components of the received reference signals are used as attributes with a single-class classification support vector machine (SCC-SVM). It is shown that the authentication performance improves with the number of antennas, and the proposed scheme provides robust authentication.

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Section: System Modelmentioning

confidence: 99%

Secure authentication in MIMO systems: exploring physical limits

Abdrabou,

Gulliver

2024

Front. Comms. Net.

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“…In addition, physical environment between Alice and Bob remains stable, although there are location differences between Bob and Eve. Therefore, the presence of multiple antennas and multipath fading results in Bob's physical layer features containing specific information that exhibits independence [29,30], which can serve as authentication evidence.…”

Section: Eve4 Eve4 Eve5 Eve5mentioning

confidence: 99%

FPLA: A Flexible Physical Layer Authentication Mechanism for Distributing Quantum Keys Securely via Wireless 5G Channels

Han

Liu

et al. 2023

Applied Sciences

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Quantum Key Distribution (QKD) is popular for establishing a native secure quantum communication network. However, existing QKD networks are built via classical wired fiber channels; it is difficult to distribute quantum keys directly into mobile phones, and no effective candidate solution is available yet. This paper presents a novel Flexible Physical Layer Authentication (FPLA) mechanism that exploits the unique characteristic of wireless signals from mobile phones to securely distribute quantum keys via wireless 5G channels. In particular, a 5G Up-Link Sounding Reference Signal (SRS)-based transmission model is developed to capture and extract the unique characteristic, which is then used to distribute quantum keys. Moreover, the model could lose accuracy due to SRS variations introduced by 5G Multiuser Multiple-Input Multiple-Output (MU-MIMO), so a dimensional transformation residual network is designed to classify legitimate and malicious user equipment (UE). An average authentication accuracy of 96.8% is proved by FPLA in multiple experiments in a 3 dB Signal-to-Noise Ratio (SNR) test environment with a training dataset of 300 samples per malicious UE. Simulation results show that FPLA is able to adapt to antenna diversity in 5G MU-MIMO systems.

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“…AI techniques can perform dimensionality reduction, denoising, and feature extraction on CSI data [145]. Therefore, the identity of wireless devices can be verified by using AI to classify CSI in ZTA [141,156,47,99].…”

Section: Automated User Authenticationmentioning

confidence: 99%

Automation and Orchestration of Zero Trust Architecture:Potential Solutions and Challenges

Cao¹,

Pokhrel²,

Zhu³

et al. 2022

Preprint

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<p>Zero Trust Architecture (ZTA) is a paradigm shift in how we protect data, stay connected, and access resources. ZTA is non-perimeter based defense, which has been emerging as a promising revolution in the cybersecurity field. It can be used to continuously maintain security by safeguarding against attacks both from inside and outside of the network system. However, automation and orchestration ZTA, an essential direction towards its seamless deployments over real-word networks, have been poorly understood in literature. In this paper, we first identify the bottlenecks, discuss the background of ZTA and compare it with traditional perimeter-based security architectures. More importantly, we present a comprehensive direction towards the automation and orchestration of ZTA by employing AI techniques. In other words, the key potential and roles of celebrates AI techniques for the automation and orchestration of ZTA are demonstrated for further exploration. Overall, in this review paper, we develop a foundational view on the challenges and potential enablers for the automation and orchestration of ZTA.</p>

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Physical-Layer Authentication Using Channel State Information and Machine Learning

Cited by 14 publications

References 23 publications

Secure authentication in MIMO systems: exploring physical limits

Secure authentication in MIMO systems: exploring physical limits

FPLA: A Flexible Physical Layer Authentication Mechanism for Distributing Quantum Keys Securely via Wireless 5G Channels

Automation and Orchestration of Zero Trust Architecture:Potential Solutions and Challenges

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