摘要
在分析了DDoS攻击的特征基础上,建立了基于数据挖掘算法的检测模型,该模型使用k-means聚类算法与Apriori关联规则对网络流量与数据包连接状态分别建立特征模型,实验表明,该检测模型能够实时有效的检测DDoS攻击.
After the analyses of the characteristics of the DDoS attack, a detection model is built based on data mining algorithm. K-means cluster algorithm and Apriori association algorithm are adopted in the detection modle to extract network traffic model and packet connection status model. Experimental results show that DDoS attacks can be detected efficiently and swiftly in the model.
出处
《江西理工大学学报》
CAS
2010年第2期33-36,共4页
Journal of Jiangxi University of Science and Technology
关键词
分布式拒绝服务攻击
聚类算法
关联规则
数据挖掘
distributed denial of service attack（DDoS ）
cluster algorithm
association algorithm
data mining
