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Signature-Based Approach for Intrusion Detection

  • Bon K. Sy
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3587)

Abstract

This research presents a data mining technique for discovering masquerader intrusion. User/system access data are used as a basis for deriving statistically significant event patterns. These patterns could be considered as a user/system access signature. Signature-based approach employs a model discovery technique to derive a reference ground model accounting for the user/system access data. A unique characteristic of this reference ground model is that it captures the statistical characteristics of the access signature, thus providing a basis for reasoning the existence of a security intrusion based on comparing real time access signature with that embedded in the reference ground model. The effectiveness of this approach will be evaluated based on comparative performance using a publicly available data set that contains user masquerade.

Keywords

Receiver Operating Characteristic Receiver Operating Characteristic Curve Intrusion Detection Event Pattern Association Pattern 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Bon K. Sy
    • 1
  1. 1.Computer Science Department, FlushingQueens College/CUNYNYU.S.A

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