Zeng, Dake, Badshah, Akhtar, Tu, Shanshan, Ai, Xin, Alasmary, Hisham, Waqas, Muhammad ORCID: https://orcid.org/0000-0003-0814-7544 and Khan, Muhammad Taimoor ORCID: https://orcid.org/0000-0002-5752-6420 (2025) Anonymous and efficient chaotic map-based authentication protocol for Industrial Internet of Things. Sensors, 25 (24):7676. ISSN 1424-8220 (Online) (doi:10.3390/s25247676)

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Abstract

The exponential growth of Internet infrastructure and the widespread adoption of smart sensing devices have empowered industrial personnel to conduct remote, real-time data analysis within the Industrial Internet of Things (IIoT) framework. However, transmitting this real-time data over public channels raises significant security and privacy concerns. To prevent unauthorized access, user authentication mechanisms are crucial in the IIoT environment. To mitigate security vulnerabilities within IIoT environments, a novel user authentication and key agreement protocol is proposed. The protocol is designed to restrict service access exclusively to authorized users of designated smart sensing devices. By incorporating cryptographic hash functions, chaotic maps, Physical Unclonable Functions (PUFs), and fuzzy extractors, the protocol enhances security and functional integrity. PUFs provide robust protection against tampering and cloning, while fuzzy extractors facilitate secure biometric verification through the integration of smart cards, passwords, and personal biometrics. Moreover, the protocol accommodates dynamic device enrollment, password and biometric updates, and smart card revocation. A rigorous formal security analysis employing the Real-or-Random (ROR) model was conducted to validate session key security. Complementary informal security analysis was performed to assess resistance to a broad spectrum of attacks. Comparative performance evaluations unequivocally demonstrate the protocol’s superior efficiency and security in comparison to existing benchmarks.

Item Type:	Article
Additional Information:	This article belongs to the Section Internet of Things.
Uncontrolled Keywords:	Industrial Internet of Things, security, privacy, authentication, key agreement, biometrics
Subjects:	Q Science > Q Science (General) Q Science > QA Mathematics Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Faculty / School / Research Centre / Research Group:	Faculty of Engineering & Science Faculty of Engineering & Science > School of Computing & Mathematical Sciences (CMS)
Last Modified:	19 Dec 2025 10:09
URI:	https://gala.gre.ac.uk/id/eprint/52019

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