Unsupervised Intrusion Detection Algorithm Based on Association Amendment

摘要：

　　Unsupervised fuzzy c-means clustering(FCM)algorithm is applied to intrusion detection so that intrusion detection system can directly deal with unlabeled original network data.Because particle swarm optimization(PSO)algorithm is easy to implement global optimum,FCM algorithm is improved based on particle swarm algorithm,in order to address the deficiencies that FCM is easy to fall into local optimum when applied to intrusion detection system.The unsupervised clustering result is further association amended and the accuracy and adaption of the intrusion detection system is improved.

关键词： intrusion detection fuzzy c-means clustering particle swarm optimization association amendment

作者: Zuohua Wang

作者单位: Department of Computer Science and Technology Nanjing University Nanjing, China

会议类型: 国际会议

会议名称: The 2014 10th International Conference on Natural Computation (ICNC 2014) and the 2014 11th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2014)(第十届自然计算和第十一届模糊系统与知识发现国际会议)

会议地点: 厦门

会议语种:英文

页码: 921-925

在线出版日期: 2014-08-19（万方平台首次上网日期，不代表论文的发表时间）