Study on Attribute Reduction Method of Network Intrusion Detection System Based on Granular Computing

摘要：

　　Based on granular computing theory, according to the problem of intrusion detection classification performance reduced by redundant attribute in high dimensional network data, an attribute reduction method of network intrusion detection system based on granular computing is given, the redundant attribute is removed under the condition of keeping the information integrity of original attribute set to reduce the attribute dimension of data.The example analysis indicates that this method reduces the training and detection time, and improves the computing efficiency of system in order to reduce the data storage, it provides a new idea for processing massive large data.

关键词： granular computing network intrusion detection system attribute reduction

作者: Leng Tianyi Li Haiyan

作者单位: International School Beijing University of Posts and Telecommunications Beijing,China School of Science University of Science and Technology Liaoning Anshan,China

会议类型: 国际会议

会议名称: 2013 International Conference on Education Technology and Management Science(ICETMS2013)2013年教育技术与管理科学国际会议

会议地点: 南京

会议语种:英文

页码: 410-412

在线出版日期: 2013-06-08（万方平台首次上网日期，不代表论文的发表时间）