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N. Ye, X. Li, Q. Chen, S. Emran, and M. Xu, “Probabilistic techniques for intrusion detection based on computer audit data,” IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans, Vol. 31, No. 4, pp. 266–274, 2001.

has been cited by the following article:

• TITLE: Self-Organized Detection of Relationships in a Network

  AUTHORS: Qurban A. Memon

  KEYWORDS: Relationship Network, Network Access, Self-Organization in Networks, Relationship Clustering

  JOURNAL NAME: International Journal of Communications, Network and System Sciences, Vol.3 No.3, March 31, 2010

  ABSTRACT: Multistate operations within a network result in high-dimensional, multivariate temporal data, and are useful for systems, which monitor access to network entities like resources, objects, etc. Efficient self organization of such multi-state network operations stored in databases with respect to relationships amongst users or between a user and a data object is an important and a challenging problem. In this work, a layer is proposed where discovered relationship patterns amongst users are classified as clusters. This information along with attributes of involved users is used to monitor and extract existing and growing relationships. The correlation is used to help generate alerts in advance due to internal user-object interactions or collaboration of internal as well as external entities. Using an experimental setup, the evolving relationships are monitored, and clustered in the database.