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A Hybrid Phish Detection Approach by Identity Discovery and Keywords Retrieval

机译:基于身份发现和关键字检索的混合式网络钓鱼检测方法

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Phishing is a significant security threat to the Internet, which causes tremendous economic loss every year. In this paper, we proposed a novel hybrid phish detection method based on information extraction (IE) and information retrieval (IR) techniques. The identity-based component of our method detects phishing webpages by directly discovering the inconsistency between their identity and the identity they are imitating. The keywords-retrieval component utilizes IR algorithms exploiting the power of search engines to identify phish. Our method requires no training data, no prior knowledge of phishing signatures and specific implementations, and thus is able to adapt quickly to constantly appearing new phishing patterns. Comprehensive experiments over a diverse spectrum of data sources with 11449 pages show that both components have a low false positive rate and the stacked approach achieves a true positive rate of 90.06% with a false positive rate of 1.95%.
机译:网络钓鱼是对互联网的重大安全威胁,每年都会造成巨大的经济损失。在本文中,我们提出了一种基于信息提取(IE)和信息检索(IR)技术的新型混合网络钓鱼检测方法。我们方法的基于身份的组件通过直接发现其身份与它们所模仿的身份之间的不一致来检测网络钓鱼网页。关键字检索组件利用IR算法,利用搜索引擎的能力来识别网络钓鱼。我们的方法不需要培训数据,不需要网络钓鱼签名的先验知识和特定的实现方式,因此能够快速适应不断出现的新网络钓鱼模式。在具有11449页的各种数据源上进行的全面实验表明,这两个组件的误报率都很低,而堆叠式方法的直报率高达90.06%,而误报率则为1.95%。

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