摘要
为了解决入侵检测模型中海量数据处理问题,降低计算复杂度,提高检测精度,提出基于最小规则自组织映射的入侵检测算法;通过在真实的入侵检测数据集上进行仿真实验,将该算法与普通椭圆补丁算法、简单矩形补丁算法以及决策树算法进行对比。结果表明,该算法在检测精度、稳定性和计算时间方面优于对比算法,验证了该算法的有效性。
To solve the problem of massive data handling in intrusion detection model,reduce the computational complexity and improve the detection accuracy,an intrusion detection algorithm based on minimum rule self-organizing mapping was proposed.By performing simulation experiments on real intrusion detection data sets,the proposed algorithm was compared with the basic ellipse patch algorithm,simple rectangle patch algorithm,and decision tree algorithm.The results show that the proposed algorithm is superior to the comparison algorithms in detection accuracy,stability,and computation time,which proves the effectiveness of the proposed algorithm.
作者
张亦辉
刘振栋
单东方
ZHANG Yihui;LIU Zhendong;SHAN Dongfang(Information Center,Shandong Polytechnic,Jinan 250104,Shandong,China;School of Computer Science and Technology,Shandong Jianzhu University,Jinan 250101,Shandong,China;School of Management Science and Engineering,Shandong University of Finance and Economics,Jinan 250014,Shandong,China)
出处
《济南大学学报（自然科学版）》
CAS
北大核心
2021年第1期10-15,共6页
Journal of University of Jinan(Science and Technology)
基金
国家自然科学基金项目(61672328)。
关键词
网络安全
入侵检测算法
自组织映射
network security
intrusion detection algorithm
self-organizing map
