%0 Journal Article
%T An Intrusion Detection Model Based on Improved Random Forests Algorithm<br>基于改进的随机森林算法的入侵检测模型
%A GUO Shan-Qing
%A GAO Cong
%A YAO Jian
%A XIE Li
%A <br>郭山清
%A 高丛
%A 姚建
%A 谢立
%J 软件学报
%D 2005
%I 
%X Coupled with the explosion of number of the network-oriented applications, Intrusion Detection as an increasingly popular area is attracting more and more research efforts. Although a number of algorithms have already been presented to tackle this problem, they are unable to achieve balanced detection performance for different types of intrusion and cannot respond as quickly as expected. Employing random forests algorithm (RFA)in intrusion detection, this paper devises an improved variation - IRFA and presents an IRFA based model for intrusion detection in information exchanged through network connections. The feasibility in balanced detection and the effectiveness of this approach are verified by experiments based on DARPA data sets.
%K intrusion detection
%K random forests algorithm
%K classified tree
%K evolutionary algorithm<br>入侵检测
%K 随机森林算法
%K 分类树
%K 进化算法
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=7735F413D429542E610B3D6AC0D5EC59&aid=6B801B4D3B3C7D6F&yid=2DD7160C83D0ACED&vid=7801E6FC5AE9020C&iid=5D311CA918CA9A03&sid=4EFBE760AF9E3A64&eid=A8B2B5CCDF243387&journal_id=1000-9825&journal_name=软件学报&referenced_num=5&reference_num=20