• DocumentCode
    3234524
  • Title

    Research on E-government Information Security Risk Assessment - Based on Fuzzy AHP and Artificial Neural Network Model

  • Author

    Wei, Guangfu ; Xin Xhang ; Zhang, Xinlan ; Huang, Zhifang

  • Author_Institution
    Sch. of Econ. & Manage., China Univ. of Geosci., Wuhan, China
  • fYear
    2010
  • fDate
    21-24 Oct. 2010
  • Firstpage
    218
  • Lastpage
    221
  • Abstract
    Information security risk assessment is essential to government for making an efficient and effective security management plan. This paper firstly established a hierarchy structure index system for E-government information systems security risk assessment based on the operationally critical threat, assets and vulnerability evaluation (OCTAVE). Considering that the previous weights selection methods mostly depend on expert experience, this paper proposes a new security risk assessment method based on FAHP and ANN. We apply this method to an actual e-government information systems and the test case proves that the proposed index system and assessment method are of effectiveness. Also, we find that this method is less time cost than only using ANN method without decreasing the accuracy of the result.
  • Keywords
    artificial intelligence; decision making; fuzzy set theory; government data processing; neural nets; risk analysis; risk management; security of data; statistical analysis; ANN method; FAHP; OCTAVE; artificial neural network model; e-government information system security risk assessment; fuzzy AHP model; hierarchy structure index system; security management plan; weight selection methods; Artificial neural networks; Electronic government; Information systems; Risk management; Security; Training; Fuzzy AHP; artificial neural network; e-government security; risk assessment;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Networking and Distributed Computing (ICNDC), 2010 First International Conference on
  • Conference_Location
    Hangzhou
  • Print_ISBN
    978-1-4244-8382-2
  • Type

    conf

  • DOI
    10.1109/ICNDC.2010.52
  • Filename
    5645431