基于SVM的中文钓鱼网站检测系统设计与实现

随着在线交易以及电子商务服务量的增加，钓鱼网站犯罪已经逐渐成为网络上最严重的犯罪形式之一。钓鱼网站主要通过假冒真实网站的页面内容以及URL地址，或者攻击某些现实网站中服务器程序上的漏洞等方式来骗取用户信用卡或银行卡账号、密码等重要私人信息资料，可能给用户带来经济上和其他方面的损失。为处理应对钓鱼网站的带来的互联网威胁，本课题将根据有效的中文钓鱼网站的检测方法，设计研发中文钓鱼网站检测系统。本课题主要采用合适中文钓鱼网站的智能检测技术，基于个人收集和反钓鱼联盟提供的大量钓鱼网站页面，建立中文钓鱼网站黑名单数据库，对基于网页内容的钓鱼网站进行分析处理，提取出能够表现出钓鱼页面的各种特征，通过利用自然语言处理，机器学习，数据挖掘，等人工智能技术，构建中文钓鱼网站检测系统，将判断待鉴别的未知网站是否是钓鱼网站。本课题主要工作和贡献包括中文钓鱼网站黑名单数据库模块的设计与实现，中文钓鱼网站的特征表达和特征选择模块的设计与实现，基于支持向量机算法的中文钓鱼网站检测分类器的设计与实现。最终使得该系统可以用于进行中文钓鱼网站的智能检测，因此该工作具有一定的研究意义与实用价值。
[主题词]  ；钓鱼网站；分类；支持向量机；特征提取
Design and Implementation for Chinese Phishing Websites Detection System Based on SVM
 

[Abstract]  With the increase in the amount of online transactions and e-commerce services, the crime of phishing websites have become one of the  most serious forms of crimes on the Internet. Phishing websites, which are mainly disguised as a real website with the fake web content and the URL or attacking some real websites loopholes in the program on the server to cheat the user for their credit card or bank card account number, password and other important private information, which may cause economic and other losses for users. To cope with the threats that phishing websites cause, in this dissertation, Chinese phishing websites detection system will be designed and developed according to some effective detection method for Chinese phishing websites. Some suitable intelligent detection technology for Chinese phishing websites is mainly adopted. A large number of phishing websites page was provided by myself and anti-phishing alliance will be used to build Chinese phishing websites blacklist database. Then web content of phishing websites is supposed to be analyzed and processed to extracted feature and representation for phishing websites. By using some Artificial intelligence technology such as Natural Language Processing, Machine Learning, Data Mining, a Chinese phishing websites detection system will be implemented to   distinguish whether an unknown website is a phishing website. The main work and contribution of my dissertation are as follows: design and implementation of Chinese phishing websites blacklist database, design and implementation of Chinese phishing websites feature representation and feature selection module, design and implementation of Chinese phishing websites detection module based on Support Vector Machine (SVM). Ultimately, the system can be used for intelligent detection of Chinese phishing websites, and the result includes some theoretic and practical values.
[Key Words]  Phishing Websites；Classification；SVM；Feature Extraction

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