计算机工程与应用2012，Vol.48Issue(32)：65-68,4.DOI:10.3778/j.issn.1002-8331.1107-0078
新的模糊核聚类入侵检测方法
New intrusion detection method based on fuzzy kernel clustering algorithm
刘永芬 1陈志安2
作者信息
- 1. 福建农林大学金山学院信息与机电工程系,福州350001
- 2. 福建电信科学技术研究院,福州350001
- 折叠
摘要
Abstract
To solve the problem of high cost in labeling the data artificially and that of the dimension effect by traditional clustering method, this paper proposes a new fuzzy support vector clustering algorithm to cope with unlabeled data. Through combining .K-means and DBSCAN algorithm to generate association matrix, setting the threshold value of constraint term to get the initial clustering, and using the fuzzy support vector domain description, the final result is achieved. The contrast experiment shows the feasibility and effectiveness of this method.关键词
网络入侵检测/模糊核聚类/支持向量Key words
network intrusion detection/ fuzzy kernel clustering/ support vector分类
信息技术与安全科学引用本文复制引用
刘永芬,陈志安..新的模糊核聚类入侵检测方法[J].计算机工程与应用,2012,48(32):65-68,4.
