期刊名称：International Journal of Security and Its Applications
印刷版ISSN：1738-9976
出版年度：2014
卷号：8
期号：2
页码：231-242
DOI：10.14257/ijsia.2014.8.2.24
出版社：SERSC
摘要：Anomaly traffic detecting using Netflow data is one of important problems in the field of network security. In this paper, we proposed an approach using MapReduce model, which was realized by means of the entropy observation and DFN (Distinct feature number) distribution deviations of traffic features under anomalies at small time scales. The MapReduce was used to deal with huge amounts of data with the aid of computer cluster processing. Experimental results show the effectiveness of the proposed approach.
关键词：Netflow; MapReduce; small time scales; traffic features
