计算机技术与发展Issue(1)：101-105,5.DOI:10.3969/j.issn.1673-629X.2016.01.021
基于改进K均值算法的入侵检测系统设计
Design of Intrusion Detection System Based on Improved K-means Algorithm
摘要
Abstract
Traditional intrusion detection system is matched to the rule base and network packet one by one. When the network is the huge increase in the amount of data,detection efficiency significantly reduces,even in the face of enormous challenges not immediately detec-ted. Data mining is a technology finds a variety of valuable information from the mass of data,data mining technology into the intrusion detection system will greatly improve efficiency and intelligence of this IDS. Focus on researching the K -means clustering algorithm in data mining for application to intrusion detection system. The K -means algorithm has some shortcomings,such as to be affected by the in-itial K value and outlier,difficulty of determining K value,highly depending on the initial center point. To overcome these disadvantages, an improved K -means clustering algorithm is proposed. And an intrusion detection system based on this is designed. The results show that the improved clustering algorithm is applied to intrusion detection,it can significantly improve the abnormality detection efficiency,and a-daptively establish the abnormal pattern database of intrusion detection,and effectively prevent the unknown intrusion and greatly reduce the false detection rate.关键词
数据挖掘/入侵检测/聚类算法/异常检测Key words
data mining/intrusion detection/clustering algorithm/anomaly detection分类
信息技术与安全科学引用本文复制引用
刘华春,候向宁,杨忠..基于改进K均值算法的入侵检测系统设计[J].计算机技术与发展,2016,(1):101-105,5.基金项目
四川省自然科学重点项目(A22012003) （A22012003）
