Advertisement

Variable Consistency Dominance-based Rough Set Approach to Security Assessment of Preference Information System

  • Liang Zhao
  • Zhi Xue
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 143)

Abstract

For the complete or incomplete preference information system, this paper proposes the multi-attribute group decision-making (MAGDM) security assessment method based on the variable consistency dominance-based rough set approach (VC-DRSA).By using the quality of sorting (QoS), this method combines VC-DRSA with the analytic hierarchy process (AHP), determines the security attribute weight and decision makers’ weight, and makes the security assessment of preference information system. Through the experiment about the stoke exchange network system and the comparison with other methods, the rationality and feasibility of the proposed method are validated.

Keywords

Variable consistency dominance-based rough set approach Security assessment Preference information system Multi-attribute group decision-making Analytic hierarchy process Quality of sorting 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Damart, S., Dias, L.C., Mousseau, V.: Supporting groups in sorting decisions: Methodology and use of a multi-criteria aggregation/disaggregation. DSS. Decis. Support. Syst. 43, 1464–1475 (2007)CrossRefGoogle Scholar
  2. 2.
    Zhai, L.Y., Khoo, L.P., Zhong, Z.W.: Dominance-based rough set approach to Kansei Engineering in product development. Expert. Syst. Appl. 36, 393–402 (2009)CrossRefGoogle Scholar
  3. 3.
    Bi, W.J., Chen, X.H.: An extended dominance-based rough set approach to group decision. In: 3rd IEEE International Conference on Wireless Communications, Networking and Mobile Computing, pp. 5753–5756. IEEE Press, New York (2007)Google Scholar
  4. 4.
    Inuiguchi, M., Miyajima, T.: Rough set based rule induction from two decision tables. Eur. J. Oper. Res. 181, 1540–1553 (2007)zbMATHCrossRefGoogle Scholar
  5. 5.
    Nagamachi, M., Okazaki, Y., Ishikawa, M.: Kansei engineering and application of the rough sets model. In: Proceedings of IMechE, pp. 763–768. PEP, London (2006)Google Scholar
  6. 6.
    Xie, G., Zhang, J.L., Lai, K.K., et al.: Variable precision rough set for group decision-making: an application. Int. J. Approx. Reason. 49, 331–343 (2008)zbMATHCrossRefGoogle Scholar
  7. 7.
    Greco, S., Matarazzo, B., Slowinski, R.: Rough approximation of a preference relation by dominance relations. Eur. J. Oper. Res. 117, 63–83 (1999)zbMATHCrossRefGoogle Scholar
  8. 8.
    Greco, S., Matarazzo, B., Slowinski, R.: Rough approximation by dominance relations. Int. J. Intell. Syst. 17, 153–171 (2002)zbMATHCrossRefGoogle Scholar
  9. 9.
    Greco, S., Matarazzo, B., Slowinski, R., et al.: Variable consistency model of dominance-based rough sets approach. In: Proceedings of Rough Sets and Current Trends in Computing 2000, pp. 170–181. Springler-Verlag, Berlin (2001)CrossRefGoogle Scholar
  10. 10.
    Błaszczyński, J., Greco, S., Slowinski, R., et al.: Monotonic variable consistency rough set approaches. Int. J. Approx. Reason. 50, 979–999 (2009)zbMATHCrossRefGoogle Scholar
  11. 11.
    Satty, T.L.: The analytic hierarchy process. McGraw-Hill, New York (1980)Google Scholar
  12. 12.
    Zhao, L., Xue, Z.: Synthetic security assessment based on variable consistency dominance-based rough set approach. High. Tech. Lett. 16, 413–421 (2010)Google Scholar
  13. 13.
    Zhao, L., Xue, Z.: Generalized dominance-based rough set approach to security evaluation with imprecise information. High. Tech. Lett. 16, 254–262 (2010)Google Scholar

Copyright information

© Springer-Verlag GmbH Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.School of Electronic and Electric EngineeringShanghai Jiaotong UniversityShanghaiChina

Personalised recommendations