钓鱼网站检测技术研究综述  

Review of the Research on Phishing Website Detection Technology

作　　者：云雷[1] 李丹[1] 王欢欢 YUN Lei;LI Dan;WANG Huanhuan(CEPREI,Guangzhou 511370,China)

机构地区：[1]工业和信息化部电子第五研究所信息安全中心,广东广州511370 [2]工业和信息化部电子第五研究所,广东广州511370

出　　处：《电子产品可靠性与环境试验》2021年第5期114-119,共6页Electronic Product Reliability and Environmental Testing

摘　　要：随着互联网的普及发展,网站在金融、社保、医疗和教育等重要领域的应用日益广泛,与此同时,钓鱼网站也呈现爆炸式增长,严重地威胁着用户的数据隐私和财产安全。由于钓鱼网站的链接与良性网站的链接极其相似,且输出形式多样,用户不易分辨,因此,钓鱼网站的检测得到了研究者的重视,现已成为网络安全领域的研究热点。围绕黑名单方法与机器学习方法介绍钓鱼网站检测技术,从静态特征与动态特征两个方面介绍钓鱼网站特征提取技术。同时,分析了现有检测技术面临的主要挑战,并对未来的重点研究方向进行了展望。With the popularization and development of the Internet,the application of websites in important fields such as finance,social insurance,medical care,and education has become increasingly widespread.At the same time,phishing websites are also showing explosive growth,which seriously threatens users’data privacy and property security.Because the links of phishing websites are very similar to the links of benign websites,and the output forms are various,users are not easy to distinguish.So,the phishing website detection has attracted the attention of researchers and has become a research hotspot in the field of network security.Phishing website detection techniques are introduced around blacklist methods and machine learning methods,and the feature extraction technology of phishing website is introduced from two aspects of static feature and dynamic feature.At the same time,the main challenges faced by the existing detection technology are analyzed,and the key research directions in the future are prospected.

关 键 词：钓鱼网站检测 黑名单 机器学习 特征提取 

分 类 号：TP393.08[自动化与计算机技术—计算机应用技术]