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Security and Privacy in 5G-IIoT Smart Factories: Novel Approaches, Trends, and Challenges

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Abstract

To implement various artificial intelligence and automation applications in smart factories, edge computing and industrial Internet of Things (IIoT) devices must be widely deployed, so as to increase the demand of coping with huge-scale and high-diversity data. Through deployment of fifth-generation (5G) networks (providing wide broadband, low latency, and massive machine type communications), industrial wireless networks, cloud, and fixed/mobile end devices in smart factories are interoperated in a harmony. However, with the huge-scale deployment of 5G networks and the IIoT in smart factories, threats and attacks against various vulnerabilities increase enormously, and cause considerable security and privacy challenges. Consequently, this article investigates crucial security and privacy issues for 5G-IIoT smart factories in three entities (i.e., physical layer, data layer and application layer), and further surveys recent approaches based on deep learning, reinforcement learning, and blockchain. In addition, this article provides future perspectives and challenges along this line of research.

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Acknowledgements

This work has been supported in part by National Science and Technology Council, Taiwan, under Grants NSTC 112-2221-E-A49-116-MY3, NSTC 111-2221-E-A49-081, MOST 109-2221-E-009-068-MY3, MOST 108-2628-E-009-008-MY3, MOST 110-2622-E-A49-004, and MOST 108-2221-E-156-003.

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Authors and Affiliations

  1. Department of Industrial Engineering and Management, National Yang Ming Chiao Tung University, Hsinchu, 300, Taiwan

    Chun-Cheng Lin, Tsai-Ting Chang & Yung-Sheng Chang

  2. Department of Business Administration, Asia University, Taichung, 413, Taiwan

    Chun-Cheng Lin

  3. Department of Medical Research, China Medical University Hospital, China Medical University, Taichung, 404, Taiwan

    Chun-Cheng Lin

  4. Department of Computer Science, Tunghai University, Taichung, 407, Taiwan

    Ching-Tsorng Tsai

  5. Department of Multimedia and Game Design, Overseas Chinese University, Taichung, 407, Taiwan

    Yu-Liang Liu

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  1. Chun-Cheng Lin
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Correspondence to Yu-Liang Liu.

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Lin, CC., Tsai, CT., Liu, YL. et al. Security and Privacy in 5G-IIoT Smart Factories: Novel Approaches, Trends, and Challenges. Mobile Netw Appl 28, 1043–1058 (2023). https://doi.org/10.1007/s11036-023-02143-5

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