%0 Journal Article
%T Anomaly Detection Based on Network Module Structure<br>基于网络模块化结构的异常发现
%A Wang Juan
%A Qin Zhi-guang
%A Liu Qiao
%A Qian Wei-zhong
%A <br>王娟
%A 秦志光
%A 刘峤
%A 钱伟中
%J 电子与信息学报
%D 2011
%I 
%X The large scale and high speed networks create massive data and have low detection accuracy. To address the problems, the idea “module” is brought from complex network into anomaly detection area. Firstly, the relations between network partition strategy and network detection accuracy are modeled, and a theoretically proof is given that partition strategy which based on network modularity is favorable for anomaly detection. Secondly, the module-based detection is proved that has higher detection rate and efficiency than network-based detection by theoretical analysis and experiments. Finally, by using flow-splitting and parallel processing technologies this approach can improve efficiency obviously.
%K Network anomaly detection
%K Network modularity
%K Flow-split<br>网络异常检测
%K 网络模块度
%K 分流
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=1319827C0C74AAE8D654BEA21B7F54D3&jid=EFC0377B03BD8D0EF4BBB548AC5F739A&aid=BC3B948C35C9ED772B992865ABE7CDF0&yid=9377ED8094509821&vid=27746BCEEE58E9DC&iid=CA4FD0336C81A37A&sid=F1A8654ADB4E656E&eid=798FBE8DE1A255B1&journal_id=1009-5896&journal_name=电子与信息学报&referenced_num=0&reference_num=14