THE APPLICATION OF ROUGH SETS ON NETWORK INTRUSION DETECTION

摘要：

With a growing amount of network information flowing, the limitations of the traditional network IDSs become more and more obvious, which can not adapt to the increasing trend of novel network attacks and data quantities.As a result, the analysis process becomes time-consuming.Fortunately, as is well known, Rough Sets reduction theory can effectively avoid redundancy and reduce extra attributes.Therefore, to solve the problems in IDSs, the paper advocates using the theory of rough set to improve the attribute reduction algorithm.Experimental results show that the number of attributes can be reduced 64％ using the proposed method.Thus, it can be concluded that the presented method can shorten detection process efficiently.

关键词： Network intrusion detection Rough sets Attributes reduction

作者: CUI-JUAN LIU

作者单位: College of Information Engineering, Shijiazhuang University of Economics, Shijiazhuang 050031, China

会议类型: 国际会议

会议名称: 2007 International Conference on Machine Learning and Cybernetics(IEEE第六届机器学习与控制论国际会议)

会议地点: 香港

会议语种:英文

页码: 3657-3660

在线出版日期: 2007-08-19（万方平台首次上网日期，不代表论文的发表时间）