IDEAS home Printed from https://ideas.repec.org/a/igg/jswis0/v19y2023i1p1-25.html
   My bibliography  Save this article

A Lightweight Cross-Domain Authentication Protocol for Trusted Access to Industrial Internet

Author

Listed:
  • Tiantian Zhang

    (Information Engineering College, Henan University of Science and Technology, Luoyang, China, & Henan International Joint Laboratory of Cyberspace Security Applications, Henan University of Science and Technology, Luoyang, China, & Henan Intelligent Manufacturing Big Data Development Innovation Laboratory, Henan University of Science and Technology, Henan Luoyang, China)

  • Zhiyong Zhang

    (Information Engineering College, Henan University of Science and Technology, Luoyang, China, & Henan International Joint Laboratory of Cyberspace Security Applications, Henan University of Science and Technology, Luoyang, China, & Henan Intelligent Manufacturing Big Data Development Innovation Laboratory, Henan University of Science and Technology, Henan Luoyang, China)

  • Kejing Zhao

    (Information Engineering College, Henan University of Science and Technology, Luoyang, China, & Henan International Joint Laboratory of Cyberspace Security Applications, Henan University of Science and Technology, Luoyang, China, & Henan Intelligent Manufacturing Big Data Development Innovation Laboratory, Henan University of Science and Technology, Henan Luoyang, China)

  • Brij B. Gupta

    (Department of Computer Science and Information Engineering, Asia University, Taichung, Taiwan, & Symbiosis Centre for Information Technology (SCIT), Symbiosis International University, Pune, India, & Lebanese American University, Beirut, Lebanon, & School of Computing, Skyline University College, Sharjah, UAE)

  • Varsha Arya

    (Varsha Arya, Department of Business Administration, Asia University, Taiwan, & Center for Interdisciplinary Research, University of Petroleum and Energy Studies (UPES), Dehradun, India, & Chandigarh University, Chandigarh, India)

Abstract

This paper proposes a hierarchical framework for industrial Internet device authentication and trusted access as well as a mechanism for industrial security state perception, and designs a cross-domain authentication scheme for devices on this basis. The scheme obtains hardware device platform configuration register (PCR) values and platform integrity measure through periodic perception, completes device identity identification and integrity measure verification when device accessing and data transmission requesting, ensures secure and trustworthy access and interoperation of devices, and designs a cross-domain authentication model for trustworthy access of devices and related security protocols. Through the security analysis, this scheme has good anti-attack abilities, and it can effectively protect against common replay attacks, impersonation attacks, and man-in-the-middle attacks.

Suggested Citation

  • Tiantian Zhang & Zhiyong Zhang & Kejing Zhao & Brij B. Gupta & Varsha Arya, 2023. "A Lightweight Cross-Domain Authentication Protocol for Trusted Access to Industrial Internet," International Journal on Semantic Web and Information Systems (IJSWIS), IGI Global, vol. 19(1), pages 1-25, January.
    • Handle: RePEc:igg:jswis0:v:19:y:2023:i:1:p:1-25
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJSWIS.333481
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Bessi, Alessandro, 2017. "On the statistical properties of viral misinformation in online social media," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 459-470.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Talwar, Shalini & Dhir, Amandeep & Kaur, Puneet & Zafar, Nida & Alrasheedy, Melfi, 2019. "Why do people share fake news? Associations between the dark side of social media use and fake news sharing behavior," Journal of Retailing and Consumer Services, Elsevier, vol. 51(C), pages 72-82.
    2. Ozbay, Feyza Altunbey & Alatas, Bilal, 2020. "Fake news detection within online social media using supervised artificial intelligence algorithms," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:igg:jswis0:v:19:y:2023:i:1:p:1-25. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Journal Editor (email available below). General contact details of provider: https://www.igi-global.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.