Intrusion Detection Models Based on Data Mining

@article{Mao2012IntrusionDM,
  title={Intrusion Detection Models Based on Data Mining},
  author={Guojun Mao and Xindong Wu and Xuxian Jiang},
  journal={Int. J. Comput. Intell. Syst.},
  year={2012},
  volume={5},
  pages={30-38}
}
Abstract Computer intrusions are taking place everywhere, and have become a major concern for information security. Most intrusions to a computer system may result from illegitimate or irregular calls to the operating system, so analyzing the system-call sequences becomes an important and fundamental technique to detect potential intrusions. This paper proposes two models based on data mining technology, respectively called frequency patterns (FP) and tree patterns (TP) for intrusion detection… CONTINUE READING
BETA

Similar Papers

Figures, Tables, Results, and Topics from this paper.

Key Quantitative Results

  • These results showed that the best intrusion detection systems had only detection rates below 70%, that is, the best intrusion detection systems can at most correctly identify 70% attack incidents in their computer systems.

References

Publications referenced by this paper.