多阶段网络钓鱼URL预测的机器学习

Khalid Amen, Mohamad Zohdy, M. Mahmoud
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引用次数: 0

摘要

网络钓鱼是一种欺诈过程,也是网络犯罪的一种形式,攻击者试图获取敏感信息以进行恶意使用。网络钓鱼者使用社会工程和技术欺骗从网络用户那里获取私人信息。以前的机器学习(ML)方法已用于检测url是否有效或无效。这项工作的目的是检测或预测网络钓鱼url的三个阶段,从有效、信息不足和无效的url开始。我们将研究由机器学习算法训练的不同潜在模型,并找出哪些模型具有更好的准确性。
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Machine Learning for Multiple Stage Phishing URL Prediction
Phishing is a fraudulent process and a form of cybercrime where an attacker tries to obtain sensitive information for malicious use. A phisher uses social engineering and technical deception to fetch private information from the web user. Previous Machine Learning (ML) approaches have been used to detect whether URLs are valid, or invalid. The purpose of this work is to detect, or predict, the three stages of Phishing URLs starting with valid, not enough info and invalid URLs. We will investigate different potential models that are trained by Machine Learning algorithms and find out which of these models has better accuracy.
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