一种基于聚类的路径伪造检测方法

发布时间：2018-04-06 05:23

  本文选题：异常检测　切入点：聚类　出处：《计算机科学》2014年08期

【摘要】：提出一种基于聚类的路径伪造检测方法。该方法将相邻时刻路由路径的变化集作为检测对象,以前缀地址所属国家为依据,对路径变化集进行聚类,引入各变化自治域的AS链接概率偏离度、中间国家出现概率和中间国家地理偏离度的定义,在此基础上引入路径级异常检测指标,综合利用这些指标检测路由中的路径伪造异常行为。选用真实的路径伪造事件数据进行实验,结果表明该检测方法较以往的检测方法更为有效、可行。
[Abstract]:A method of path forgery detection based on clustering is proposed.In this method, the change set of the routing path at adjacent times is taken as the detection object, and the path change set is clustered according to the country of prefix address, and the deviation degree of as link probability is introduced in each change autonomous region.Based on the definition of probability of occurrence in intermediate countries and geographical deviation degree of intermediate countries, the path-level anomaly detection indexes are introduced to detect path forgery anomaly behavior in the route synthetically.The experimental results show that this method is more effective and feasible than the previous methods.
【作者单位】： 电子工程学院;
【基金】：安徽省自然科学基金(1208085QF107)资助
【分类号】：TP393.04
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本文编号：1718153