IDEAS home Printed from https://ideas.repec.org/a/sae/intdis/v18y2022i5p15501329221097588.html
   My bibliography  Save this article

A hybrid trust model based on communication and social trust for vehicular social networks

Author

Listed:
  • Na Fan
  • Shuai Shen
  • Chase Q Wu
  • Junfeng Yao

Abstract

Vehicular social networks are emerging hybrid networks that combine traditional vehicular networks and social networks, with two key types of nodes, that is, vehicles and drivers. Since vehicle behaviors are controlled or influenced by drivers, the trustworthiness of a vehicle node is essentially determined by its own communication behaviors and its driver’s social characteristics. Therefore, human factors should be considered in securing the communication in vehicular social networks. In this article, we propose a hybrid trust model that considers both communication trust and social trust. Within the proposed scheme, we first construct a communication trust model to quantify the trust value based on the interactions between vehicle nodes, and then develop a social trust model to measure the social trust based on the social characteristics of vehicle drivers. Based on these two trust models, we compute the combined trust assessment of a vehicle node in vehicular social networks. Extensive simulations show that the proposed hybrid trust model improves the accuracy in evaluating the trustworthiness of vehicle nodes and the efficiency of communication in vehicular social networks.

Suggested Citation

  • Na Fan & Shuai Shen & Chase Q Wu & Junfeng Yao, 2022. "A hybrid trust model based on communication and social trust for vehicular social networks," International Journal of Distributed Sensor Networks, , vol. 18(5), pages 15501329221, May.
  • Handle: RePEc:sae:intdis:v:18:y:2022:i:5:p:15501329221097588
    DOI: 10.1177/15501329221097588
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/15501329221097588
    Download Restriction: no

    File URL: https://libkey.io/10.1177/15501329221097588?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    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:sae:intdis:v:18:y:2022:i:5:p:15501329221097588. 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: SAGE Publications (email available below). General contact details of provider: .

    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.