论文标题
使用机器学习技术检测网络钓鱼
Phishing Detection Using Machine Learning Techniques
论文作者
论文摘要
互联网已成为我们生活中必不可少的一部分，但是，它也为匿名进行诸如网络钓鱼之类的恶意活动提供了机会。网络钓鱼者试图通过社会工程学欺骗受害者，或创建模拟网站以窃取信息ID，用户名，个人和组织的密码等信息。尽管已经提出了许多方法来检测网络钓鱼网站，但网络钓鱼者已经进化了他们摆脱这些检测方法的方法。检测这些恶意活动的最成功方法之一是机器学习。这是因为大多数网络钓鱼攻击都有一些共同的特征，可以通过机器学习方法识别。在本文中，我们比较了用于预测网络钓鱼网站的多种机器学习方法的结果。
The Internet has become an indispensable part of our life, However, It also has provided opportunities to anonymously perform malicious activities like Phishing. Phishers try to deceive their victims by social engineering or creating mock-up websites to steal information such as account ID, username, password from individuals and organizations. Although many methods have been proposed to detect phishing websites, Phishers have evolved their methods to escape from these detection methods. One of the most successful methods for detecting these malicious activities is Machine Learning. This is because most Phishing attacks have some common characteristics which can be identified by machine learning methods. In this paper, we compared the results of multiple machine learning methods for predicting phishing websites.
