Adaptive intrusion detection with data mining

@article{Hossain2003AdaptiveID,
  title={Adaptive intrusion detection with data mining},
  author={Mahmood Hossain and Susan M. Bridges and Rayford B. Vaughn},
  journal={SMC'03 Conference Proceedings. 2003 IEEE International Conference on Systems, Man and Cybernetics. Conference Theme - System Security and Assurance (Cat. No.03CH37483)},
  year={2003},
  volume={4},
  pages={3097-3103 vol.4}
}
A major constraint of an anomaly-based intrusion detection system (IDS) lies in its inability to adapt to distinguish these changes from intrusive behavior. To overcome these obstacles, the normal profile must be updated at regular intervals. The naive approach of exhaustively recomputing the normal profile is often not viable and can incorporate patterns of intrusive behavior as normal. We address technical issues and present an adaptive data mining framework for anomaly detection. We employ a… CONTINUE READING

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References

Publications referenced by this paper.
SHOWING 1-9 OF 9 REFERENCES

, and V . Sr inivq “ An a , dap - tive algorithm for incremental mining of association rules ”

N. Sarda Nandlal
  • Proc . 13 th Ann . IFIP WG 11 . 3 Working Conf . on Database Security

An efficient algorithm for the incremental upda - tion of association rules in large databases ”

S. Bodagala Thomas, K. Alsabti, S. Ranka

    Fast algorithms for mining association rules ” Fuzzy data mining and genetic algorithms applied to intrusion detection “

    A. Swami

      Incre - mental maintenance techniques for discovered classification rules ”

      M. Mohania C. Rainsford, J. Roddick