• DocumentCode
    3107994
  • Title

    A Bayesian Network Approach to Detecting Privacy Intrusion

  • Author

    An, Xiangdong ; Jutla, Dawn ; Cercone, Nick

  • Author_Institution
    Dept. of Finance, Inf. Syst. & Manage. Sci., Saint Mary´´s Univ., Halifax, NS
  • fYear
    2006
  • fDate
    18-22 Dec. 2006
  • Firstpage
    73
  • Lastpage
    76
  • Abstract
    Personal information privacy could be compromised during information collection, transmission, and handling. In information handling, privacy could be violated by both the inside and the outside intruders. Though, within an organization, private data are generally protected by the organization´s privacy policies and the corresponding platforms for privacy practices, private data could still be misused intentionally or unintentionally by individuals who have legitimate access to them in the organization. In this paper, we propose a Bayesian network-based method for insider privacy intrusion detection in database systems
  • Keywords
    Bayes methods; data mining; data privacy; security of data; Bayesian network approach; database systems; information handling; privacy intrusion detection; private data; Bayesian methods; Cryptography; Data privacy; Database systems; Intelligent agent; Intrusion detection; Operating systems; Protection; Transaction databases; Uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Web Intelligence and Intelligent Agent Technology Workshops, 2006. WI-IAT 2006 Workshops. 2006 IEEE/WIC/ACM International Conference on
  • Conference_Location
    Hong Kong
  • Print_ISBN
    0-7695-2749-3
  • Type

    conf

  • DOI
    10.1109/WI-IATW.2006.6
  • Filename
    4053207