url分类的机器学习算法

Sabah Salam Khaduair Al Zirjawi, Hawraa Jaafar Murad Kashkool, A. Ibrahim, Mona Idan Ali Al
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引用次数: 0

摘要

网络钓鱼是一种技术,用来收集用户的敏感数据(密码或信用卡信息),以备将来滥用,冒充一个值得信赖的来源。它经常利用用户的易受骗性,使用户乍一看不会察觉,在最坏的情况下,攻击者在用户不知情的情况下维护用户的数据。通常,URL是我们了解网站的第一个也是最简单的信息。因此,设计区分有害url和良性url的算法是合乎逻辑的。此外,访问和下载网站的材料可能是耗时的,并涉及下载潜在危险信息的危险。机器学习技术用于在指定为一组特征的url集合上训练模型,然后预测并将url分类为良性或危险。这项技术使我们能够快速识别和避免可能存在危险的url。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Machine Learning Algorithms for URLs Classification
Phishing is a technique used to collect sensitive data from a user (password or credit card information) for future misuse by posing as a trustworthy source. It often takes advantage of the user’s gullibility in ways that the user will not detect at first look, and in the worst-case scenario, the attacker maintains the user’s data without the user’s awareness. Typically, the URL is the first and simplest piece of information we know about a website. As a result, it is logical to design algorithms for distinguishing harmful from benign URLs. Additionally, accessing and downloading the website’s material may be time-consuming and involves the danger of downloading potentially hazardous information. Machine Learning techniques are used to train a model on a collection of URLs specified as a set of characteristics and then predict and categorize the URLs as benign or dangerous. This technology enables us to identify and avoid possibly dangerous URLs shortly.
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