Abstract
Based on the Fuzzy C-Means algorithm, we proposed the PSO-FCM algorithm combining the Fuzzy C-Means with PSO. Then KDD cup 99 dataset was applied to algorithm, the experiments indicate that the PSO-FCM algorithm can avoid the inherent shortcomings of the FCM algorithm, and has higher detection performance with detection rate rising and false alarm rate falling. In addition, we compare the performance of PSO-FCM with other clustering; it can be more satisfactory results.
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Acknowledgments
The authors would like to thank the editors and the anonymous reviewers whose invaluable comments and suggestions led to greatly improved manuscript.
This work was supported in part by the Education Department of Henan Province Science & Technology Research Project (Grant No. 14B520052).
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Zhang, Z., Gu, B. (2016). Intrusion Detection Network Based on Fuzzy C-Means and Particle Swarm Optimization. In: Qi, E. (eds) Proceedings of the 6th International Asia Conference on Industrial Engineering and Management Innovation. Atlantis Press, Paris. https://doi.org/10.2991/978-94-6239-145-1_12
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DOI: https://doi.org/10.2991/978-94-6239-145-1_12
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