Efficient K-means Algorithm in Intrusion Detection
Available Online March 2017.
- https://doi.org/10.2991/msam-17.2017.43How to use a DOI?
- intrusion detection, K-means, cluster, average density
- In order to improve the detection rate of invasion, reduce false detection rate and put forward a method based on density and maximum distance of k means clustering algorithm, the clustering results used in intrusion detection, improved the original algorithm in the choice of initial clustering center, simplify the computational complexity of the algorithm. Finally simulation experiments using KDD Cup 99 data set. Results show that the model can obtain ideal intrusion detection rate and false detection rate.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Wenjun Yang PY - 2017/03 DA - 2017/03 TI - Efficient K-means Algorithm in Intrusion Detection BT - 2017 2nd International Conference on Modelling, Simulation and Applied Mathematics (MSAM2017) PB - Atlantis Press SP - 193 EP - 195 SN - 1951-6851 UR - https://doi.org/10.2991/msam-17.2017.43 DO - https://doi.org/10.2991/msam-17.2017.43 ID - Yang2017/03 ER -