文章基本信息

标题：Detecting malicious URLs using binary classification through adaboost algorithm
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作者：Firoz Khan ; Jinesh Ahamed ; Seifedine Kadry 等
期刊名称：International Journal of Electrical and Computer Engineering
电子版ISSN：2088-8708
出版年度：2020
卷号：10
期号：1
页码：997-1005
DOI：10.11591/ijece.v10i1.pp997-1005
出版社：Institute of Advanced Engineering and Science (IAES)
摘要：Malicious Uniform Resource Locator (URL) is a frequent and severe menace to cybersecurity. Malicious URLs are used to extract unsolicited information and trick inexperienced end users as a sufferer of scams and create losses of billions of money each year. It is crucial to identify and appropriately respond to such URLs. Usually, this discovery is made by the practice and use of blacklists in the cyber world. However, blacklists cannot be exhaustive, and cannot recognize zero-day malicious URLs. So to increase the observation of malicious URL indicators, machine learning procedures should be incorporated. This study aims to discuss the exposure of malicious URLs as a binary classification problem using machine learning through an AdaBoost algorithm.
关键词：AdaBoost algorithm;Binary classification problem;Blacklists;Machine learning;Malicious Uniform Resource Locator