e-space
Manchester Metropolitan University's Research Repository

    IIS: Intelligent identification scheme of massive IoT devices

    Liu, Jie, Sun, Yi, Xu, Fengkai, Yu, Keping, Bashir, Ali Kashif ORCID logoORCID: https://orcid.org/0000-0001-7595-2522 and Liu, Zhaoli (2021) IIS: Intelligent identification scheme of massive IoT devices. In: 2021 IEEE 45th Annual Computers, Software, and Applications Conference (COMPSAC), 12 July 2021 - 16 July 2021, Madrid, Spain.

    [img]
    Preview
    Accepted Version
    Download (384kB) | Preview

    Abstract

    Device identification is of great importance in system management and network security. Especially, it is the priority in industrial internet of things (IIoT) scenario. Since there are massive devices producing various kinds of information in manufacturing process, the robustness, reliability, security and real-time control of the whole system is based on the identification of the massive IIoT devices. Previous IIoT device identification solutions are mostly based on a centralized architecture, which brings a lot of problems in scalability and security. In addition, most traditional identification systems can only identify inherent types of devices which is not suitable for the adaptive device management in IIoT. In order to solve these problems, this paper proposes a Intelligent Identification Scheme(IIS) of Massive IoT Devices, a completely distributed intelligent identification scheme of massive IIoT devices. The scheme changes the traditional centralized architecture and realizes more efficient clustering identification of massive IIoT devices. Moreover, IIS can identify more and more types of devices intelligently with the continuous learning ability since the identification model is constantly updated according to the ledger which is maintained by all gateways collaboratively. We also conduct experiments to evaluate the performance of IIS based on the data obtained from real IIoT devices, which proves that IIS is efficient in device identification and intelligent for the adaptive device management in IIoT.

    Impact and Reach

    Statistics

    Activity Overview
    6 month trend
    0Downloads
    6 month trend
    0Hits

    Additional statistics for this dataset are available via IRStats2.

    Altmetric

    Repository staff only

    Edit record Edit record