特征树阀值检测算法应对电信欺诈  

Fraud Detection In Telecom Business Based On Feature Tree Analysis

作　　者：李春霖[1] 李文高 

机构地区：[1]北京邮电大学信息与通信工程学院,北京100876 [2]北京东方文骏软件科技有限公司

出　　处：《软件》2011年第1期8-13,共6页Software

摘　　要：电信网络日益复杂,这增加了电信营运的难度,并且大额欺诈和恶意欠费的状况使电信运营收入存在较大的风险。本文在数据挖掘技术、基于聚类的层次分析算法等理论基础上,采用了欺诈特征树阀值检测算法来应对电信欺诈,防范电信运营收入的流失。该算法将用户的数据特征项构建成欺诈特征树,采用关系数据模式来组织用户的欺诈特征项,并设定结点阀值作为检测判断的依据,依照用户最后的欺诈度值判断用户是否欺诈。算法简单高效,系统占用较少的内存并获得了较高的准确率。In this paper,we focus on the need for telecommunication business about the fraud problem,to guarantee the revenue issue.The paper describes the antifraud system based on Data Mining theory and fraud feature tree construction.Data Ming provides an overall method framework in solving the problem while fraud feature tree construction is a detail on how the fraud detection is proceeding.Three elements come first before the feature tree is successfully constructed：telecommunication fraud characters analysis,subscriber data analysis,basic understanding on telecom business.The final solving method named ＇fraud verdict by nodes in feature tree ＇.Its inspiration comes from the FT（feature tree） in BIRCH（Balanced Iterative Reducing and Clustering using Hierarchies）,abnormity detection base on clustering analysis,related data modal research in Data Base.The creative points in this paper also include the data analysis methods.We use efficient data process tools,such as MATLAB and office data analysis tools.They turn the illogic discrete and meaningless data to vivid graphs that reveal the latent deception in telecom subscribers＇ behavior.

关 键 词：数据处理 电信欺诈 数据挖掘 特征树 软件 

分 类 号：TP31[自动化与计算机技术—计算机软件与理论]