Hammad, Muhammad, Badshah, Akhtar, Abbas, Ghulam, Alasmary, Hisham, Waqas, Muhammad ORCID: https://orcid.org/0000-0003-0814-7544 and Khan, Waseem Ahmed (2023) A provable secure and efficient authentication framework for smart manufacturing industry. IEEE Access, 11. pp. 67626-6763. ISSN 2169-3536 (Online) (doi:10.1109/ACCESS.2023.3290913)

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Abstract

Smart manufacturing is transforming the manufacturing industry by enhancing productivity and quality, driving growth in the global economy. The Internet of Things (IoT) has played a crucial role in realizing Industry 4.0, where machines can communicate and interact in real-time. Despite these advancements, security remains a major challenge in developing and deploying smart manufacturing. As cyber-attacks become more prevalent, researchers are making security a top priority. Although IoT and Industrial IoT (IIoT) are used to establish smart industries, these systems remain vulnerable to various types of attacks. To address these security issues, numerous authentication methods have been proposed. However, many of these methods are vulnerable to known attacks, such as physical security, privileged-insider, and impersonation attacks, or have high computational and communication costs, making them unsuitable for resource-limited IoT devices. Therefore, in this paper, we present a new approach to mutual authentication between the flexible manufacturing system unit, the user, and the server. It enables secure communication in an IIoT-enabled system, which represents the smart manufacturing industry. This security is achieved through the establishment of session keys. The security analysis shows the effectiveness of the proposed solution in resisting various types of attacks. Additionally, a comparison with other existing schemes reveals that our proposal outperforms them in terms of performance.

Item Type:	Article
Uncontrolled Keywords:	smart manufacturing; security; authentication; Internet of Things; resource-limited IoT devices; mutual authentication
Subjects:	H Social Sciences > HD Industries. Land use. Labor > HD61 Risk Management Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software
Faculty / School / Research Centre / Research Group:	Faculty of Engineering & Science Faculty of Engineering & Science > School of Computing & Mathematical Sciences (CMS)
Last Modified:	18 Oct 2023 11:42
URI:	http://gala.gre.ac.uk/id/eprint/44486

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