Intrusion Detection using an Ensemble of Classification Methods

@inproceedings{GovindarajanIntrusionDU,
  title={Intrusion Detection using an Ensemble of Classification Methods},
  author={M. Govindarajan and R. M. Chandrasekaran}
}
in the past decade is the ensemble method, which finds highly accurate classifier by combining many moderately accurate component classifiers. This paper addresses using an ensemble of classification methods for intrusion detection. Due to increasing incidents of cyber attacks, building effective intrusion detection systems are essential for protecting information systems security, and yet it remains an elusive goal and a great challenge. In this research work, new hybrid classification method… CONTINUE READING
Highly Cited
This paper has 26 citations. REVIEW CITATIONS

Citations

Publications citing this paper.
Showing 1-10 of 14 extracted citations

Analysis and evaluation of hybrid intrusion detection system models

2015 International Conference on Computers, Communications, and Systems (ICCCS) • 2015
View 3 Excerpts
Highly Influenced

Hybrid evolutionary algorithms for data classification in intrusion detection systems

2015 IEEE/ACIS 16th International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD) • 2015
View 1 Excerpt

Intrusion detection using error correcting output code based ensemble

2014 14th International Conference on Hybrid Intelligent Systems • 2014
View 2 Excerpts

References

Publications referenced by this paper.
Showing 1-7 of 7 references

Adaptive neurofuzzy intrusion detection system

K Shah, N Dave, +3 authors S. Sanyal
IEEE International Conference on Information Technology : Coding and Computing ( ITCC ’ 04 ) • 2004
View 1 Excerpt

Experiments with a new boosting algorithm

AK Ghosh
1996

Similar Papers

Loading similar papers…