Practical Applicability of PLA for Industrial Wireless Networks: Gaps and Directions
The rapid transformation of Industrial Cyber-Physical System (ICPS) has introduced significant cyber security challenges, particularly in the context of ICPS. Wireless networks are a critical component of these systems, but their open nature makes them vulnerable to security threats. Physical Layer Authentication (PLA) algorithms based on Channel State Information (CSI) are essential complements to existing security technologies in wireless networks. However, their practical application faces challenges such as restricted sampling rates and uneven sampling interval, which result in low-precision CSI, significant random phase offsets, and signal distortion. This study aims to explore the feasibility of deploying and applying existing representative algorithms on industrial wireless commercial devices. According to characteristics of authentication algorithms and the adopted authentication features, we selected five of the latest physical layer authentication algorithms including supervised, semi-supervised, and unsupervised algorithms and deployed them on commercial devices that comply with the WIA-FA standard. We conducted systematic experiments focusing on the motion parameters of devices, the CSI data sampling frequency, the interference caused by worker movement, the surface materials of the devices, and the types of attacks. This study explores the ability of these algorithms to resist attacks and environmental interference in commercial devices and industrial scenarios. Extensive experimental data were collected, and the results indicate that existing authentication algorithms still need improvement to meet the requirements of industrial applications. The experiment findings and the summarized application challenges of these algorithms provide significant guidance for future research and practical industrial implementations.
Authors
- Ming Zhan (ORCID: https://orcid.org/0000-0002-2626-7374)
- Fuwen Wei (ORCID: https://orcid.org/0000-0002-5233-1288)
- Qi Wang (ORCID: https://orcid.org/0000-0002-6749-3351)
- Ke Wang (ORCID: https://orcid.org/0000-0001-7661-2597)
- Wei Liang (ORCID: https://orcid.org/0000-0002-4730-017X)
Institutions
- Shenyang Institute of Automation (CN)
- Chinese Academy of Sciences (CN)
- Shandong Normal University (CN)
- Taizhou University (CN)
Publication Details
- Journal
- IEEE Network
- Published
- 2025-02-13
- DOI
- https://doi.org/10.1109/mnet.2025.3541591
- Primary Topic
- Wireless Body Area Networks
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China