Adaptive Physical Layer Authentication Using Machine Learning With Antenna Diversity

Abdrabou, Mohammed; Gulliver, Thomas Aaron

doi:10.1109/tcomm.2022.3196648

Cited by 25 publications

(6 citation statements)

References 55 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…ML methods have been employed for energy management in malls and hotels [24], energy reduction in buildings [27], heating and cooling demand management in buildings [28], property market price analysis [29], building energy consumption analysis [31], power load analysis [33], urban traffic control [34], time series prediction [36], antenna design prediction [38], adaptive authentication for wireless networks [41], distributed SG performance enhancement [39], energy efficiency [40], and load maintenance and peak shaving in buildings [42].…”

Section: Methods For Dpmentioning

confidence: 99%

Energy Management in Modern Buildings Based on Demand Prediction and Machine Learning—A Review

Moghimi,

Gulliver,

Thirumai Chelvan

2024

Energies

Self Cite

View full text Add to dashboard Cite

show abstract

Section: Methods For Dpmentioning

confidence: 99%

Energy Management in Modern Buildings Based on Demand Prediction and Machine Learning—A Review

Moghimi,

Gulliver,

Thirumai Chelvan

2024

Energies

Self Cite

View full text Add to dashboard Cite

show abstract

“…The AR improves with the number of antenna (Abdrabou and Gulliver, 2022b), and the corresponding PPV increases, so…”

Section: Performance Evaluationmentioning

confidence: 99%

“…The authentication performance can be improved with antenna diversity (Abdrabou and Gulliver, 2022b;. This is indicated by the First, a single-input multiple-output system (SIMO) and independent channels based on user location and mobility are considered.…”

Section: Information-theoretic Plamentioning

confidence: 99%

“…The performance is evaluated using the confusion matrix which includes true positive (TP), the acceptance of A, true negative (TN), the rejection of S, false negative (FN), the erroneous rejection of A, and false positive (FP), the erroneous acceptance of S. The evaluation metrics are the missed detection rate (MDR), false alarm rate (FAR), precision or positive predictive value (PPV), false discovery rate (FDR), and authentication rate (AR) (Senigagliesi et al, 2020;Abdrabou and Gulliver, 2022b):…”

Section: Performance Evaluationmentioning

confidence: 99%

See 1 more Smart Citation

Secure authentication in MIMO systems: exploring physical limits

Abdrabou,

Gulliver

2024

Front. Comms. Net.

Self Cite

View full text Add to dashboard Cite

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.

show abstract

“…Qiu et al [25] presented a data-adaptive matrix to capture time-varying channel characteristics and combined it with Convolutional Neural Network (CNN) to achieve physical layer security authentication. Abdrabou and Gulliver [26] presented an adaptive lightweight physical layer authentication scheme using 5G Up-Link CSI features as classification evidence. This scheme can improve accuracy through the utilization of antenna diversity.…”

Section: Physical Layer Authentication (Pla)mentioning

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

View full text Add to dashboard Cite

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.

show abstract

Adaptive Physical Layer Authentication Using Machine Learning With Antenna Diversity

Cited by 25 publications

References 55 publications

Energy Management in Modern Buildings Based on Demand Prediction and Machine Learning—A Review

Energy Management in Modern Buildings Based on Demand Prediction and Machine Learning—A Review

Secure authentication in MIMO systems: exploring physical limits

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

Contact Info

Product

Resources

About