A Trust Model with Statistical Foundation

  • Jianqiang Shi
  • Gregor v. Bochmann
  • Carlisle Adams
Conference paper

DOI: 10.1007/0-387-24098-5_11

Part of the IFIP International Federation for Information Processing book series (IFIPAICT, volume 173)
Cite this paper as:
Shi J., v. Bochmann G., Adams C. (2005) A Trust Model with Statistical Foundation. In: Dimitrakos T., Martinelli F. (eds) Formal Aspects in Security and Trust. IFIP International Federation for Information Processing, vol 173. Springer, Boston, MA

Abstract

The widespread use of the Internet signals the need for a better understanding of trust as a basis for secure on-line interaction. In the face of increasing uncertainty and risk, users and machines must be allowed to reason effectively about the trustworthiness of other entities. In this paper, we propose a trust model that assists users and machines with decision-making in online interactions by using past behavior as a predictor of likely future behavior. We develop a general method to automatically compute trust based on self-experience and the recommendations of others. Furthermore, we apply our trust model to several utility models to increase the accuracy of decision-making in different contexts of Web Services.

Key words

trust utility decision making 
Download to read the full conference paper text

Copyright information

© International Federation for Information Processing 2005

Authors and Affiliations

  • Jianqiang Shi
    • 1
  • Gregor v. Bochmann
    • 2
  • Carlisle Adams
    • 2
  1. 1.Systems ScienceUniversity of OttawaOttawaCanada
  2. 2.School of Information Technology and Engineering (SITE)University of OttawaOttawaCanada

Personalised recommendations