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Determining the Failure Level for Risk Analysis in an e-Commerce Interaction

  • Omar Khadeer Hussain
  • Elizabeth Chang
  • Farookh Khadeer Hussain
  • Tharam S. Dillon
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4891)

Abstract

Before initiating a financial e-commerce interaction over the World Wide Web, the initiating agent would like to analyze the possible Risk in interacting with an agent, to ascertain the level to which it will not achieve its desired outcomes in the interaction. By analyzing the possible risk, the initiating agent can make an informed decision of its future course of action with that agent. To determine the possible risk in an interaction, the initiating agent has to determine the probability of failure and the possible consequences of failure to its resources involved in the interaction. In this chapter as a step towards risk analysis, we propose a methodology by which the initiating agent can determine beforehand the probability of failure in interacting with an agent, to achieve its desired outcomes.

Keywords

Risk assessing agent Risk assessed agent FailureLevel and Failure scale 

References

  1. 1.
    Mayer, R.C., Davis, J.H., Schoorman, F.D.: An interactive model for organizational trust. Academy of Management Review 20(3), 709–734 (1995)Google Scholar
  2. 2.
    Greenland, S.: Bounding analysis as an inadequately specified methodology. Risk Analysis 24(5), 1085–1092 (2004)CrossRefGoogle Scholar
  3. 3.
    Chang, E., Dillon, T., Hussain, F.K.: Trust and Reputation for Service-Oriented Environments: Technologies for Building Business Intelligence and Consumer Confidence, 1st edn. John Wiley and Sons Ltd., Chichester (2006)CrossRefGoogle Scholar
  4. 4.
    Hussain, O.K., Chang, E., Hussain, F.K., Dillon, T.S.: Risk in Decentralized Communications. In: International Workshop on Privacy Data Management in Conjunction with 21st International Conference on Data Engineering, p. 1198 (2005)Google Scholar
  5. 5.
    Carter, J., Ghorbani, A.A.: Towards a formalization of Trust. Web Intelligence and Agent Systems 2(3), 167–183 (2004)Google Scholar
  6. 6.
    Wang, Y., Varadharajan, V.: A Time-based Peer Trust Evaluation in P2P E-commerce Environments. In: Zhou, X., Su, S., Papazoglou, M.P., Orlowska, M.E., Jeffery, K. (eds.) WISE 2004. LNCS, vol. 3306, pp. 730–735. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  7. 7.
    Wang, Y., Varadharajan, V.: Two-phase Peer Evaluation in P2P E-commerce Environments. In: Proceedings of the 2005 IEEE International Conference on e-Technology, e-Commerce and e-Service, Hong Kong, pp. 654–657 (2005)Google Scholar
  8. 8.
    Fan, J.C.: Trust and Electronic Commerce - A Test of an E-Bookstore. In: Proceedings of the IEEE International Conference on e-business Engineering, Shanghai, pp. 110–117 (2006)Google Scholar
  9. 9.
    Wojcik, M., Eloff, J.H.P., Venter, H.S.: Trust Model Architecture: Defining Prejudice by Learning. In: Fischer-Hübner, S., Furnell, S., Lambrinoudakis, C. (eds.) TrustBus 2006. LNCS, vol. 4083, pp. 182–191. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  10. 10.
    Su, C., Zhang, H., Bi, F.: A P2P-based Trust Model for E-Commerce. In: Proceedings of the IEEE International Conference on e-business Engineering, Shanghai, pp. 118–122 (2006)Google Scholar
  11. 11.
    Koutrouli, E., Tsalgatidou, A.: Reputation-Based Trust Systems for P2P Applications: Design Issues and Comparison Framework. In: Fischer-Hübner, S., Furnell, S., Lambrinoudakis, C. (eds.) TrustBus 2006. LNCS, vol. 4083, pp. 152–161. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  12. 12.
    Chien, H., Lin, R.: Identity-based Key Agreement Protocol for Mobile Ad-hoc Networks Using Bilinear Pairing. In: Proceedings of the IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing, Taichung, Taiwan, vol. 1, pp. 520–528 (2006)Google Scholar
  13. 13.
    Hussain, F.K., Chang, E., Dillon, T.: Trustworthiness and CCCI Metrics for Assigning Trustworthiness. International Journal of Computer Science Systems and Engineering 19(2), 173–189 (2004)Google Scholar
  14. 14.
    Cornelli, F., Damiani, E., Vimercati, S.C., Paraboschi, S., Samarati, P.: Choosing Reputable Servents in a P2P Network. In: Proceedings of the International WWW Conference, Honolulu, vol. (11), pp. 376–386 (2002)Google Scholar
  15. 15.
    Weiss, N.A.: A Course in Probability. Pearson Education, Inc., USA (2006)Google Scholar
  16. 16.
    Wang, Y., Lin, F.: Trust and Risk Evaluation of Transactions with Different Amounts in Peer-to-Peer E-commerce Environments. In: Proceedings of the IEEE International Conference on e-Business Engineering, Shanghai, China, pp. 102–109 (2006)Google Scholar
  17. 17.
    Hussain, O.K., Chang, E., Hussain, F.K., Dillon, T.: A Methodology for Determining the Creditability of the Recommending Agents. In: Gabrys, B., Howlett, R.J., Jain, L.C. (eds.) KES 2006. LNCS (LNAI), vol. 4253, pp. 1119–1127. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  18. 18.
    Hussain, O.K., Chang, E., Hussain, F.K., Dillon, T.S.: A methodology for risk measurement in e-transactions. International Journal of Computer Science Systems and Engineering 21(1), 17–31 (2006)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Omar Khadeer Hussain
    • 1
  • Elizabeth Chang
    • 1
  • Farookh Khadeer Hussain
    • 1
  • Tharam S. Dillon
    • 1
  1. 1.Digital Ecosystems and Business Intelligence InstituteCurtin University of TechnologyPerthAustralia

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