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Advanced Persistent Threats and Their Defense Methods in Industrial Internet of Things: A Survey

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  • Chenquan Gan

    (School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
    School of Cyber Security and Information Law, Chongqing University of Posts and Telecommunications, Chongqing 400065, China)

  • Jiabin Lin

    (School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China)

  • Da-Wen Huang

    (College of Computer Science, Sichuan Normal University, Chengdu 610101, China)

  • Qingyi Zhu

    (School of Cyber Security and Information Law, Chongqing University of Posts and Telecommunications, Chongqing 400065, China)

  • Liang Tian

    (School of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, China)

Abstract

The industrial internet of things (IIoT) is a key pillar of the intelligent society, integrating traditional industry with modern information technology to improve production efficiency and quality. However, the IIoT also faces serious challenges from advanced persistent threats (APTs), a stealthy and persistent method of attack that can cause enormous losses and damages. In this paper, we give the definition and development of APTs. Furthermore, we examine the types of APT attacks that each layer of the four-layer IIoT reference architecture may face and review existing defense techniques. Next, we use several models to model and analyze APT activities in IIoT to identify their inherent characteristics and patterns. Finally, based on a thorough discussion of IIoT security issues, we propose some open research topics and directions.

Suggested Citation

  • Chenquan Gan & Jiabin Lin & Da-Wen Huang & Qingyi Zhu & Liang Tian, 2023. "Advanced Persistent Threats and Their Defense Methods in Industrial Internet of Things: A Survey," Mathematics, MDPI, vol. 11(14), pages 1-23, July.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:14:p:3115-:d:1194286
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    References listed on IDEAS

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    1. Chien-Ta Bruce Ho & Desheng Dash Wu & David L. Olson, 2009. "A Risk Scoring Model And Application To Measuring Internet Stock Performance," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 8(01), pages 133-149.
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