• DocumentCode
    1669681
  • Title

    A Classification of Trust Computation Models for Service-Oriented Internet of Things Systems

  • Author

    Jia Guo ; Ing-Ray Chen

  • fYear
    2015
  • Firstpage
    324
  • Lastpage
    331
  • Abstract
    Future Internet of Things (IoT) systems will connect the physical world into cyberspace everywhere and everything via billions of smart objects and are expected to have a high economic impact. To date there is little work on trust computation in IoT environments for security enhancement, especially for dealing with misbehaving owners of IoT devices that provide services to other IoT devices in the system. In this paper we classify trust computation models to-date for IoT systems. Our approach is to classify existing trust computation models based on five design dimensions: trust composition, trust propagation, trust aggregation, trust update, and trust formation. We summarize advantages and drawbacks of each dimension´s options, and highlight the effectiveness of defense mechanisms against malicious attacks. We also summarize the most and least studied trust computation techniques in the literature and provide insight on the effectiveness of trust computation techniques as applying to IoT systems. Finally, we identify gaps in IoT trust computation research and suggest future research directions.
  • Keywords
    Internet of Things; security of data; service-oriented architecture; IoT devices; cyberspace; defense mechanisms; design dimensions; physical world; security enhancement; service-oriented Internet of Things systems; smart objects; trust aggregation; trust composition; trust computation models; trust formation; trust propagation; trust update; Classification tree analysis; Computational modeling; Context; Peer-to-peer computing; Performance evaluation; Quality of service; Internet of things (IoT); security; social IoT; trust;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Services Computing (SCC), 2015 IEEE International Conference on
  • Conference_Location
    New York, NY
  • Print_ISBN
    978-1-4673-7280-0
  • Type

    conf

  • DOI
    10.1109/SCC.2015.52
  • Filename
    7207370