现代电子技术2017，Vol.40Issue(4)：28-31,4.DOI:10.16652/j.issn.1004-373x.2017.04.008
基于粗糙集的公共网络入侵检测方法研究
Research of public network intrusion detection method based on rough set theory
摘要
Abstract
Traditional method exists high redundancy,large dimension,poor accuracy and so on in the process of public network intrusion data detection. In order to improve the real⁃time performance and effectiveness of public network security pro⁃tection,a public network detection method based on the improved rough set theory is put forward to detect and screen the data which has invasion risk,optimize the detecting accuracy based on rough set concept,and reduce the information loss. The MDLP operational criterion is adopted to complete the discretization processing of the data. The genetic algorithm is used to car⁃ry on the data reduction,derive data classification rules and identify the intrusion data. The simulation results show that the pro⁃posed intrusion data detection method is more effective in the aspects of intrusion detection rate and error rate in comparison with the traditional algorithm.关键词
网络入侵数据检测/离散化处理/遗传算法/数据约简Key words
network intrusion data detection/neural network/genetic algorithm/data reduction分类
信息技术与安全科学引用本文复制引用
庞帮艳,张艳敏..基于粗糙集的公共网络入侵检测方法研究[J].现代电子技术,2017,40(4):28-31,4.基金项目
国家自然科学基金（11601304）；河南省教育技术装备和实践教育研究课题 （）
