基于最大隶属度原则的恶意节点检测方法  

Maximum membership degree based malicious nodes detection

作　　者：邹宽城[1] 欧阳园玲[1] 牛春诚[1] 邹祎 

机构地区：[1]长春工业大学计算机科学与工程学院,吉林长春130012 [2]大连消防工程有限公司,辽宁大连116013

出　　处：《长春工业大学学报》2012年第5期529-532,共4页Journal of Changchun University of Technology

基　　金：吉林省科技厅自然科学基金资助项目(20101528)

摘　　要：对选择性转发、hello洪泛的特征行为建模,抽象出4个与此两类恶意节点密切相关的属性,利用最大隶属度原则对节点进行分类。仿真结果表明,该方法能够以较低的误检率对网络中一定数量的传感节点进行正确的分类。The model is established based on the node characteristics of the selective forwarding and hello flooding, and four attributes relating to the nodes are abstracted. The nodes are classified with the maximum membership degree principle and the corresponding simulation results show that the method can assort some sensor nodes with a rather low false detection rate.

关 键 词：恶意节点 选择性转发 hello洪泛 最大隶属度 

分 类 号：N39[自然科学总论]