论文标题
基于特征选择的新加权合奏模型用于网络钓鱼检测
A new weighted ensemble model for phishing detection based on feature selection
论文作者
论文摘要
网络钓鱼攻击是一种网络攻击，攻击者在该攻击中发送假沟通以吸引人类受害者提供个人信息或证书。网站网站标识可以帮助访客避免成为这些袭击的受害者。网络钓鱼问题是每天增加，并且没有一个解决方案可以适当地减轻所有漏洞，因此使用了许多技术。在本文中，我们提出了一个合奏模型，该模型将多个基本模型与基于权重的投票技术相结合。此外，我们在数据集上应用了特征选择方法和标准化，并在应用任何特征选择之前和之后比较了结果。
A phishing attack is a sort of cyber assault in which the attacker sends fake communications to entice a human victim to provide personal information or credentials. Phishing website identification can assist visitors in avoiding becoming victims of these assaults. The phishing problem is increasing day by day, and there is no single solution that can properly mitigate all vulnerabilities, thus many techniques are used. In this paper, We have proposed an ensemble model that combines multiple base models with a voting technique based on the weights. Moreover, we applied feature selection methods and standardization on the dataset effectively and compared the result before and after applying any feature selection.
