| 基于异常特征的钓鱼网站URL检测技术 |
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| 引用本文： | 黄华军,钱亮,王耀钧.基于异常特征的钓鱼网站URL检测技术[J].信息网络安全,2012(1):23-25,67. |
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| 作者姓名： | 黄华军 钱亮 王耀钧 |
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| 作者单位： | 中南林业科技大学计算机与信息工程学院,湖南长沙410004 |
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| 基金项目： | 国家自然科学基金项目[61073191]; 湖南省自然科学基金资助项目[10JJ4043,10JJ5062]; 湖南省教育厅资助项目[08B091]; 湖南省科技重大专项项目[2010J05]; 湖南省科技计划重点项目[2010NK2003];湖南省科技计划项目[2010TZ4012] |
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| 摘 要： | 典型的网络钓鱼是采用群发垃圾邮件,欺骗用户点击钓鱼网站URL地址,登录并输入个人机密信息的一种攻击手段。文章通过分析钓鱼网站URL地址的结构和词汇特征,提出一种基于异常特征的钓鱼网站URL检测方法。抽取钓鱼网站URL地址中4个结构特征、8个词汇特征,组成12个特征的特征向量,用SVM进行训练和分类。对PhishTank上7291条钓鱼网站URL分类实验,检测出7134条钓鱼网站URL,准确率达到97.85%。
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| 关 键 词： | 网络钓鱼 钓鱼网站URL 支持向量机 特征向量 |
Detection of Phishing URL Based on Abnormal Feature |
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| HUANG Hua-Jun,QIAN Liang,WANG Yao-Jun.Detection of Phishing URL Based on Abnormal Feature[J].Netinfo Security,2012(1):23-25,67. |
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| Authors: | HUANG Hua-Jun QIAN Liang WANG Yao-Jun |
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| Affiliation: | (Department of computer and information engineering Central South University of Forestry and Technology,Changsha Hunan 410004,China) |
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| Abstract: | Phishing tries to lure her victim into clicking a phishing URL pointing to a spoof page via spam-email to harvest financial information.In this paper,a novel method is proposed to detect phishing URL based on abnormal feature.The feature vector is constructed with 12 features to model the SVM,which 4 features are the structure feature of the phishing URL,8 features are lexical feature.The method can correct to classify 7134 phishing URLs of 7291downloaded in PhishTank achieve,and the correct ratio of detection is 97.85%. |
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| Keywords: | Phishing Phishing URL SVM feature vector |
| 本文献已被 CNKI 维普 等数据库收录！ |
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