A Lightweight Mutual Authentication and Privacy-preservation Scheme for Intelligent Wearable Devices in Industrial-CPS

Mian Ahmad Jan, Fazlullah Khan, Rahim Khan, Spyridon Mastorakis, Varun G. Menon, Paul Watters, Mamoun Alazab

    Research output: Contribution to journalArticlepeer-review

    Abstract

    Industry 5.0 is the digitalization, automation and data exchange of industrial processes that involve artificial intelligence, Industrial Internet of Things (IIoT), and Industrial Cyber-Physical Systems (I-CPS). In healthcare, I-CPS enables the intelligent wearable devices to gather data from the real-world and transmit to the virtual world for decision-making. I-CPS makes our lives comfortable with the emergence of innovative healthcare applications. Similar to any other IIoT paradigm, I-CPS capable healthcare applications face numerous challenging issues. The resource-constrained nature of wearable devices and their inability to support complex security mechanisms provide an ideal platform to malevolent entities for launching attacks. To preserve the privacy of wearable devices and their data in an I-CPS environment, we propose a lightweight mutual authentication scheme. \blue{Our scheme is based on client-server interaction model that uses symmetric encryption for establishing secured sessions among the communicating entities. After mutual authentication, the privacy risk associated with a patient data is predicted using an AI-enabled Hidden Markov Model (HMM). We analyzed the robustness and security of our scheme using Burrows-Abadi-Needham (BAN) logic. This analysis shows that the use of lightweight security primitives for the exchange of session keys makes the proposed scheme highly resilient in terms of security, efficiency, and robustness. Finally, the proposed scheme incurs nominal overhead in terms of processing, communication and storage and is capable to combat a wide range of adversarial threats.

    Original languageEnglish
    Pages (from-to)5829-5839
    Number of pages10
    JournalIEEE Transactions on Industrial Informatics
    Volume17
    Issue number8
    Early online dateDec 2020
    DOIs
    Publication statusPublished - Aug 2021

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