Research on the Intrusion Detection Method Based on Differentiated Cluster Center Offset Measure

摘要：

　　In this paper,a kind of local outlier mining method based on differentiated cluster center offset measure is proposed through which the outlier degree of sample can be calculated by use of the normal behavior model constructed by normal data sample and the preset anomaly threshold value,and whether the testing sample belong to intrusion behavior can thus be determined.Furthermore,KDD99 data set is also utilized to test the said method,and the experimental results show that the method proposed in this paper possesses higher detection rate and lower false alarm rate.

关键词： Intrusion detection Anomaly detection Outlier mining Cluster center offset

作者: Yu Chen Hao Chun Qing Nian

作者单位: School of Information Science and Engineering,Lanzhou University,Lanzhou,China Lanzhou Municipal Public Security Bureau,Lanzhou,China

会议类型: 国际会议

会议名称: 2017第三届机械、电子和信息技术工程国际会议(ICMITE 2017)

会议地点: 成都

会议语种:英文

页码: 1-5

在线出版日期: 2017-12-16（万方平台首次上网日期，不代表论文的发表时间）