• DocumentCode
    2532870
  • Title

    FEMRA: Fuzzy Expert Model for Risk Assessment

  • Author

    Sendi, Alireza Shameli ; Jabbarifar, Masoume ; Shajari, Mehdi ; Dagenais, Michel

  • Author_Institution
    Ecole Polytech. de Montreal Montreal, Montreal, QC, Canada
  • fYear
    2010
  • fDate
    9-15 May 2010
  • Firstpage
    48
  • Lastpage
    53
  • Abstract
    Risk assessment is a major part of the ISMS Process. The Information Security Management System standards specify guidelines and a general framework for risk assessment. In many existing standards, such as NIST and ISO27001, risk assessment is described however, while these standards present some guidelines, there are no details on how to implement it in an organization. In a complex organization, risk assessment is a complicated process and involves a lot of assets. In this paper, we present the FEMRA model, which uses fuzzy expert systems to assess risk in organizations. The risk assessment varies considerably with the context, the metrics used as dependent variables, and the opinions of the persons involved. Fuzzy logic thus represents an excellent model for this application. Organizations can use FEMRA as a tool to improve the ISMS implementation. One of the interesting characteristics of FEMRA is that it can represent each risk with a numerical value. The managers can detect higher risks by comparing these values and develop a good strategy to reduce them.
  • Keywords
    fuzzy logic; risk management; security of data; FEMRA; fuzzy expert model for risk assessment; fuzzy logic; information security management system standards; Authentication; Biometrics; Data privacy; Data security; Entropy; Fingerprint recognition; Information security; Polynomials; Protection; Risk management; asset; fuzzy; risk assessment; threat; vulnerability;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Internet Monitoring and Protection (ICIMP), 2010 Fifth International Conference on
  • Conference_Location
    Barcelona
  • Print_ISBN
    978-1-4244-6726-6
  • Type

    conf

  • DOI
    10.1109/ICIMP.2010.15
  • Filename
    5476890