Adaptive Physical-Layer Authentication for IoT in MIMO Communication Systems Using Support Vector Machine

Abdrabou, Mohammed; Gulliver, Thomas Aaron

doi:10.1109/jiot.2023.3282214

Cited by 4 publications

(1 citation statement)

References 39 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this paper, the SCC-SVM algorithm proposed by Schölkopf et al (2001) is employed. SCC-SVM computes a decision function f which encompasses the majority of the training data [Senigagliesi et al (2020); Abdrabou and Gulliver (2022c); Abdrabou and Gulliver, 2022a;Abdrabou and Gulliver, 2023]. First, the following optimization problem is solved (Hoang et al, 2021); (Schölkopf et al, 2001):…”

Section: Single-class Classification Support Vector Machinementioning

confidence: 99%

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