基于模拟区域划分自学习的P2P-Grid入侵检测算法  

Based on the Simulation of the Learning Division of P2P-Grid Intrusion Detection Algorithm

作　　者：黄艾卿[1] 

机构地区：[1]百色学院数学与计算机信息工程系,广西百色533000

出　　处：《科技通报》2013年第2期215-217,共3页Bulletin of Science and Technology

基　　金：2010年国家自然科学基金项目(61063046)

摘　　要：提出了一种基于模拟区域划分自学习的P2P-Grid入侵检测算法,通过对得到人各种多源入侵特征建立一个小区间,在区间内运用模糊关联规则的自学习方法,对其进行检测,由于区域内的特征类似,因此特征的特点更为突出。实验表明,该方法保证了P2P-Grid模型的安全,取得了满意的结果。This paper proposes a simulated based on the division of the learning P2P-Grid intrusion detection algorithm,based on all kinds of more people get source invasion to establish a community characteristics between,in the range of fuzzy association rules since learning method,to detect the,because the area of similar characteristics,so the characteristics of features is more prominent.Experiments show that the method to ensure the safety of the P2P-Grid model,and achieved satisfactory results

关 键 词：网络攻击 关联决策 模糊差异聚类 

分 类 号：TP37[自动化与计算机技术—计算机系统结构]