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Robust and efficient three-factor authentication solution for WSN-based industrial IoT deployment

delete2024-12-01
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PRE
AI
K
Khalid Mahmood
M
Muhammad Asad Saleem *
Z
Zahid Ghaffar
S
Salman Shamshad
A
Ashok Kumar Das
M
Mohammed J. F. Alenazi
DOI:10.1016/j.iot.2024.101372delete
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摘要

摘要

En 中文
The relentless advancements in Cyber-Physical Systems (CPS) and Wireless Sensor Networks (WSN) have paved the way for various practical applications across networking, public safety, smart transportation, and industrial sectors. The Industrial Internet of Things (IIoT) integrates these technologies into complex, interconnected environments where vast amounts of data are transmitted between devices and systems. However, the inherent openness of communication channels in IIoT systems introduces distinctive security and privacy vulnerabilities, where malevolent entities can effortlessly intercept, forge, or delete communication messages. These vulnerabilities are exacerbated by the critical nature of industrial applications, where breaches can lead to significant operational disruptions or safety hazards To address these challenges, several authentication protocols have been proposed. Nevertheless, many of these protocols remain susceptible to various security attacks. To ensure privacy and security in IIoT environments, we introduce a robust and efficient authentication protocol for a WSN-based IIoT environment. This protocol preserves the privacy of information transmitted among all entities and provides an effective solution for securing this sensitive information. Additionally, we present a detailed security analysis of the proposed protocol to formally and informally demonstrate its security strength. The performance analysis is carried out to compare the proposed protocol against existing related protocols, with results unequivocally demonstrating that our protocol offers enhanced privacy and security with reduced costs.
Keyword:
Mutual authentication
Authentication solution
Privacy
Security
Industrial Internet of Things
Wireless Sensor Network

期刊

Internet of Things 封面图
Internet of Things
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7.6
论文数:
1.9K
被引数:
6.9K

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U
University of Lahore
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3.4K
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K
King Saud University
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3.4W
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International Institute of Information Technology Hyderabad
学者数:
779
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被引数: 5
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national yunlin university science & technology
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3.2K
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被引数: 1
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