Adaptive real-time anomaly detection using inductively generated sequential patterns

@article{Teng1990AdaptiveRA,
  title={Adaptive real-time anomaly detection using inductively generated sequential patterns},
  author={H. S. Teng and K. Chen and S. C. Lu},
  journal={Proceedings. 1990 IEEE Computer Society Symposium on Research in Security and Privacy},
  year={1990},
  pages={278-284}
}
  • H. S. Teng, K. Chen, S. C. Lu
  • Published 1990
  • Computer Science
  • Proceedings. 1990 IEEE Computer Society Symposium on Research in Security and Privacy
  • A time-based inductive learning approach to the problem of real-time anomaly detection is described. This approach uses sequential rules that characterize a user's behavior over time. A rulebase is used to store patterns of user activities, and anomalies are reported whenever a user's activity deviates significantly from those specified in the rules. The rules in the rulebase characterize either the sequential relationships between security audit records or the temporal properties of the… CONTINUE READING
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