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Detection and Prevention of Phishing Websites using Machine Learning Approach

机译:使用机器学习方法检测和预防网络钓鱼网站

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Phishing costs Internet user's lots of dollars per year. It refers to exploiting weakness on the user side, which is vulnerable to such attacks. The phishing problem is huge and there does not exist only one solution to minimize all vulnerabilities effectively, thus multiple techniques are implemented. In this paper, we discuss three approaches for detecting phishing websites. First is by analyzing various features of URL, second is by checking legitimacy of website by knowing where the website is being hosted and who are managing it, the third approach uses visual appearance based analysis for checking genuineness of website. We make use of Machine Learning techniques and algorithms for evaluation of these different features of URL and websites. In this paper, an overview about these approaches is presented.
机译:网络钓鱼费用每年互联网用户的大量美元。它指的是利用用户方面的弱点,这易于这种攻击。网络钓鱼问题是巨大的,只有一个解决方案只能有效地最小化所有漏洞,因此实现了多种技术。在本文中,我们讨论了检测网络钓鱼网站的三种方法。首先是通过分析URL的各种特征,第二是通过了解网站被托管并管理它的位置来检查网站的合法性,第三种方法使用基于视觉外观的分析来检查网站的真实性。我们利用机器学习技术和算法来评估URL和网站的这些不同的功能。在本文中,提出了关于这些方法的概述。

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