基于改进的TrustRank算法的钓鱼网站检测

doi:10.11959/j.issn.1000-0801.2018046

电信科学 ›› 2018, Vol. 34 ›› Issue (3): 86-94.doi: 10.11959/j.issn.1000-0801.2018046

基于改进的TrustRank算法的钓鱼网站检测

韩浩,刘博文,林果园()

中国矿业大学计算机科学与技术学院，江苏徐州 221116

修回日期:2018-01-15 出版日期:2018-03-01 发布日期:2018-04-02
作者简介:韩浩（1993-），男，中国矿业大学计算机科学与技术学院硕士生，主要研究方向为信息安全。|刘博文（1993-），男，中国矿业大学计算机科学与技术学院硕士生，主要研究方向为云计算和信息安全。|林果园（1975-），男，博士，中国矿业大学计算机科学与技术学院副教授、硕士生导师、信息安全系主任、信息安全竞赛指导委员会副主任，主要研究方向为网络空间安全、移动互联及其安全、云计算及其安全、信息系统及其安全、基于位置服务、矿井信息化等。
基金资助:
江苏省产学研前瞻性联合研究项目(BY2016026-04)

Detection of phishing websites based on the improved TrustRank algorithm

Hao HAN,Bowen LIU,Guoyuan LIN()

School of Computer Science and Technology,China University of Mining and Technology,Xuzhou 221116,China

Revised:2018-01-15 Online:2018-03-01 Published:2018-04-02
Supported by:
Production and Research Prospective Joint Research Project of Jiangsu Province(BY2016026-04)

摘要/Abstract

摘要：

钓鱼检测方式一般只是通过比较网页间特征的相似度判断钓鱼网站，容易被攻击者根据特征提取过程反检测。因此，提出依据网页之间的关系来检测钓鱼网站，通过设立网页集合、结合钓鱼网站与其他网站间的链接关系改进TrustRank算法来检测钓鱼网站。实验证明，改进的TrustRank算法可以将钓鱼网站的信任值集中在一个范围内，并且与其他方法相比具有较低的误判率、漏判率和较高的速度，可以很好地检测钓鱼网站。

关键词: 钓鱼网站, TrustRank, 网页关系, 链接关系

Abstract:

Anti-phishing methods just generally detect phishing sites based on comparing the similarity of pages features,which could be anti-detected when attackers are clear about the extraction process of features.Therefore,a method based on web pages relationship was proposed to detect phishing websites.According to this method,phishing websites were detected by an improved TrustRank algorithm which set up a collection of web pages and used the link relationship between phishing websites and other websites.Experiments show that the improved TrustRank algorithm can focus the trust values of phishing websites on some range with the lower false positive rate,the lower false negative rate and the higher speed compared to other methods.

Key words: phishing website, TrustRank, web page relationship, link relationship

中图分类号:

TP182

韩浩,刘博文,林果园. 基于改进的TrustRank算法的钓鱼网站检测[J]. 电信科学, 2018, 34(3): 86-94.

Hao HAN,Bowen LIU,Guoyuan LIN. Detection of phishing websites based on the improved TrustRank algorithm[J]. Telecommunications Science, 2018, 34(3): 86-94.

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检测方法	准确率（AC）	误判率（ET）	漏判率（LT）
改进的TrustRank	98.42%	0.347%	1.124%
图形挖掘与信念传播	97.53%	0.992%	1.764%
页面异常特征检测	97.86%	2.023%	1.526%
统计机器学习分类器	98.03%	1.017%	1.407%
易受攻击网站的URL的相关性	97.68%	1.331%	1.653%

检测方法	有效速率（D_rate）
图形挖掘与信念传播	0.902
页面异常特征检测	0.887
统计机器学习分类器	0.851
易受攻击网站的URL的相关性	0.809

基于改进的TrustRank算法的钓鱼网站检测

Detection of phishing websites based on the improved TrustRank algorithm

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