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基于行为分析的钓鱼页面检测技术研究
引用本文:赵功勋,陈运,杨义先.基于行为分析的钓鱼页面检测技术研究[J].成都信息工程学院学报,2014,29(5):464-470.
作者姓名:赵功勋  陈运  杨义先
作者单位:1. 成都信息工程学院计算机学院,四川成都,610225
2. 北京邮电大学,北京,100876
基金项目:国家自然科学基金资助项目,四川省科技支撑计划重点资助项目,感谢成都市高校院所科技成果转化项目,深圳市产学研合作项目(CXY201106240019A)对本文的资助
摘    要:针对通过黑白名单匹配的检测方法检测钓鱼页面准确率低的特点,提出基于钓鱼者行为的图状链接结构特征,对钓鱼页面进行分析,引入数据挖掘的频繁子图挖掘算法,对数据库中积累的数万个钓鱼页面进行子图模式挖掘,提取钓鱼页面的共同子图结构特征,检测网络钓鱼行为。实验结果发现,在加入了子图特征的钓鱼页面检测方法中,检出率能达到80%.因此,基于行为的钓鱼页面检测提高了钓鱼页面检测的能力,并且挖掘出的子图模式为钓鱼者的行为提供了依据。

关 键 词:信息安全  网络安全  钓鱼  行为分析  数据挖掘  频繁子图

Technique of Detection Phishing Page Detection based on Behavior Analysis
ZHAO Gong-xun,CHEN Yun,YANG Yi-xian.Technique of Detection Phishing Page Detection based on Behavior Analysis[J].Journal of Chengdu University of Information Technology,2014,29(5):464-470.
Authors:ZHAO Gong-xun  CHEN Yun  YANG Yi-xian
Institution:ZHA0 Gong-xun,CHEN Yun,YANG Yi-xian( 1.College of Computer Science, Chengdu University of Information Technology , Chengdu 610225, China; 2.Beijing University of Posts and Telecommunications ,Beijing 100876, China)
Abstract:For the accuracy of testing phfishing pages matched by the black and white lists are relatively low,.So in this paper,we putPutting forward to analysisanalyse of the link structure of anglers in phfishing pages based on the graph-like behavior,introduceintroducing data mining algorithm for mining frequent sub-graphs,minemining tens of thousands of phishing pages accumulated in the database based on sub-graphs pattern,extractextracting the structural features of the commonsame sub-graphs in the phfishing page.structural features,Andand then thedetecting behaviors of phishing pages are detected.Experiment results show that Experimentally found that detection of phfishing page based on the subgraph feature in the phfishing pages can approach to eighty percents.So,detecting phishing pages detection based on the behavior analysis can improve the ability to detect phishing pages and the excavated sub-graphs model provides a basis for anglers behavior.
Keywords:information safety  network security  phishing  behavior analysis  data mining  frequent subtree
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