• DocumentCode
    653871
  • Title

    Trust assessment in social participatory networks

  • Author

    Amintoosi, Haleh ; Allahbakhsh, Mohammad ; Kanhere, S. ; Niazi Torshiz, Masood

  • Author_Institution
    Sch. of Comput. Sci. & Eng., Univ. of New South Wales, Sydney, NSW, Australia
  • fYear
    2013
  • fDate
    Oct. 31 2013-Nov. 1 2013
  • Firstpage
    437
  • Lastpage
    442
  • Abstract
    Leveraging social networks as an underlying infrastructure for participatory sensing systems provides an effective means to have access to a reasonable number of participants, which is essential for the success of this new and exciting paradigm. Another important issue is assessing the quality of the contributions prepared by the participants, who are, on the other hand, the social network members. In this paper, we propose a trust framework for social participatory sensing systems. Our framework is aimed at quantifying the trustworthiness of contributions by considering the quality of the raw sensor readings contributed and the trustworthiness of the user contributing the sensor data, and combining them via a fuzzy inference engine to arrive at a final trust score for a contribution. It also assigns a reputation score to each user. Extensive simulations demonstrate the efficacy of our framework.
  • Keywords
    fuzzy reasoning; social networking (online); trusted computing; fuzzy inference engine; social participatory networks; social participatory sensing systems; trust assessment; user contribution trustworthiness; Fuzzy logic; Participatory Sensing; Trust;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer and Knowledge Engineering (ICCKE), 2013 3th International eConference on
  • Conference_Location
    Mashhad
  • Print_ISBN
    978-1-4799-2092-1
  • Type

    conf

  • DOI
    10.1109/ICCKE.2013.6682806
  • Filename
    6682806