IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i6p3048-d514563.html
   My bibliography  Save this article

AIS Meets IoT: A Network Security Mechanism of Sustainable Marine Resource Based on Edge Computing

Author

Listed:
  • Han-Chieh Chao

    (Department of Electrical Engineering, National Dong Hwa University, Hualien 974301, Taiwan)

  • Hsin-Te Wu

    (Department of Computer Science and Information Engineering, National Ilan University, Yilan 260007, Taiwan)

  • Fan-Hsun Tseng

    (Department of Technology Application and Human Resource Development, National Taiwan Normal University, Taipei 10610, Taiwan)

Abstract

The sustainable utilization of marine resources is a vital issue to enrich marine life and to prevent species extinction caused by overfishing. Nowadays, it is common that commercial and smaller vessels are equipped with an Automatic Identification System (AIS) and GPS for better vessel tracking to avoid vessel collision as well as mayday calls. Additionally, governments can monitor vessels’ sea activities through AIS messages, stopping them from overfishing or tracking if any vessel has caused marine pollution. However, because AIS devices cannot guarantee data security, they are susceptible to malicious attacks such as message modification or an illegitimate identity faking a distress signal that causes other vessels to change their course. Given the above, a comprehensive network security system of a sustainable marine environment should be proposed to ensure secure communication. In this paper, a stationary IoT-enabled (Internet of Things) vessel tracking system of a sustainable marine environment is proposed. The system combines network security, edge computing, and tracking management. It offers the following functions: (1) The IoT-based vessel tracking system tracks each aquafarmer’s farming zone and issues periodic warning to prevent vessel collision for pursuing a sustainable marine environment; (2) the system can serve as a relay station that evaluates whether a vessel’s AIS data is correct; (3) the system detects abnormal behavior and any irregular information to law enforcement; (4) the system’s network security mechanism adopts a group key approach to ensure secure communication between vessels; and (5) the proposed edge computing mechanism enables the tracking system to perform message authentication and analysis, and to reduce computational burden for the remote or cloud server. Experiment results indicate that our proposed system is feasible, secure, and sustainable for the marine environment, and the tendered network security mechanism can reduce the computational burden while still ensuring security.

Suggested Citation

  • Han-Chieh Chao & Hsin-Te Wu & Fan-Hsun Tseng, 2021. "AIS Meets IoT: A Network Security Mechanism of Sustainable Marine Resource Based on Edge Computing," Sustainability, MDPI, vol. 13(6), pages 1-14, March.
  • Handle: RePEc:gam:jsusta:v:13:y:2021:i:6:p:3048-:d:514563
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/6/3048/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/13/6/3048/
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Irena Jurdana & Nikola Lopac & Nobukazu Wakabayashi & Hongze Liu, 2021. "Shipboard Data Compression Method for Sustainable Real-Time Maritime Communication in Remote Voyage Monitoring of Autonomous Ships," Sustainability, MDPI, vol. 13(15), pages 1-22, July.
    2. Tomáš Loveček & Lenka Straková & Katarína Kampová, 2021. "Modeling and Simulation as Tools to Increase the Protection of Critical Infrastructure and the Sustainability of the Provision of Essential Needs of Citizens," Sustainability, MDPI, vol. 13(11), pages 1-18, May.
    3. Sanjeev Kimothi & Asha Thapliyal & Rajesh Singh & Mamoon Rashid & Anita Gehlot & Shaik Vaseem Akram & Abdul Rehman Javed, 2023. "Comprehensive Database Creation for Potential Fish Zones Using IoT and ML with Assimilation of Geospatial Techniques," Sustainability, MDPI, vol. 15(2), pages 1-16, January.

    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:gam:jsusta:v:13:y:2021:i:6:p:3048-:d:514563. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.