Document Type

Article

Publication Date

2022

DOI

10.1016/j.hcc.2022.100067

Publication Title

High-Confidence Computing

Volume

2

Issue

3

Pages

100067 (1-6)

Abstract

Physical layer security has attracted lots of attention with the expansion of wireless devices to the edge networks in recent years. Due to limited authentication mechanisms, MAC spoofing attack, also known as the identity attack, threatens wireless systems. In this paper, we study a new type of MAC spoofing attack, the virtual MAC spoofing attack, in a tight environment with strong spatial similarities, which can create multiple counterfeits entities powered by the virtualization technologies to interrupt regular services. We develop a system to effectively detect such virtual MAC spoofing attacks via the deep learning method as a countermeasure. A deep convolutional neural network is constructed to analyze signal level information extracted from Channel State Information (CSI) between the communication peers to provide additional authentication protection at the physical layer. A significant merit of the proposed detection system is that this system can distinguish two different devices even at the same location, which was not well addressed by the existing approaches. Our extensive experimental results demonstrate the effectiveness of the system with an average detection accuracy of 95%, even when devices are co-located.

Comments

© 2022 The Authors.

This is an open access article under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) license.

Original Publication Citation

Jiang, P., Wu, H., & Xin, C. (2022). A channel state information based virtual MAC spoofing detector. High-Confidence Computing, 2(3), 1-6, Article 100067. https://doi.org/10.1016/j.hcc.2022.100067

ORCID

0000-0002-2178-6888 (Jiang)

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