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Article

Graph Layer Security: Encrypting Information via Common Networked Physics

1
School of Aerospace, Transport and Manufacturing, Cranfield University, Bedford MK43 0AL, UK
2
Department of Information Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China
3
The Alan Turing Institute, London NW1 2DB, UK
*
Author to whom correspondence should be addressed.
Academic Editors: Leandros Maglaras, Helge Janicke and Mohamed Amine Ferrag
Sensors 2022, 22(10), 3951; https://doi.org/10.3390/s22103951
Received: 27 April 2022 / Revised: 19 May 2022 / Accepted: 20 May 2022 / Published: 23 May 2022
(This article belongs to the Topic Cyber Security and Critical Infrastructures)
The proliferation of low-cost Internet of Things (IoT) devices has led to a race between wireless security and channel attacks. Traditional cryptography requires high computational power and is not suitable for low-power IoT scenarios. Whilst recently developed physical layer security (PLS) can exploit common wireless channel state information (CSI), its sensitivity to channel estimation makes them vulnerable to attacks. In this work, we exploit an alternative common physics shared between IoT transceivers: the monitored channel-irrelevant physical networked dynamics (e.g., water/oil/gas/electrical signal-flows). Leveraging this, we propose, for the first time, graph layer security (GLS), by exploiting the dependency in physical dynamics among network nodes for information encryption and decryption. A graph Fourier transform (GFT) operator is used to characterise such dependency into a graph-bandlimited subspace, which allows the generation of channel-irrelevant cipher keys by maximising the secrecy rate. We evaluate our GLS against designed active and passive attackers, using IEEE 39-Bus system. Results demonstrate that GLS is not reliant on wireless CSI, and can combat attackers that have partial networked dynamic knowledge (realistic access to full dynamic and critical nodes remains challenging). We believe this novel GLS has widespread applicability in secure health monitoring and for digital twins in adversarial radio environments. View Full-Text
Keywords: cyber-physical systems; wireless security; sensor network; infrastructure health monitoring; graph signal processing cyber-physical systems; wireless security; sensor network; infrastructure health monitoring; graph signal processing
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MDPI and ACS Style

Wei, Z.; Wang, L.; Sun, S.C.; Li, B.; Guo, W. Graph Layer Security: Encrypting Information via Common Networked Physics. Sensors 2022, 22, 3951. https://doi.org/10.3390/s22103951

AMA Style

Wei Z, Wang L, Sun SC, Li B, Guo W. Graph Layer Security: Encrypting Information via Common Networked Physics. Sensors. 2022; 22(10):3951. https://doi.org/10.3390/s22103951

Chicago/Turabian Style

Wei, Zhuangkun, Liang Wang, Schyler Chengyao Sun, Bin Li, and Weisi Guo. 2022. "Graph Layer Security: Encrypting Information via Common Networked Physics" Sensors 22, no. 10: 3951. https://doi.org/10.3390/s22103951

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