Abstract: Internet has been a huge part of our day to day life. Since we are highly depended on Internet for all our daily activities, we are prone to cybercrimes. URL-based phishing attacks are one of the major threats facing by internet users. It is a way of fraudulent communication to steal the confidential data of user.Attackers mainly target people and reputed organizations, by tricking them to click on the URLs that seems to be secured and hence steal personal information of user or by injecting malware into machines.Researchers are constantly making several attempts to improve the accuracy and make model efficient.
In this paper, we aim to study and review various machine learning algorithms along with the datasets, that are used to detect legitimacy of the URL.The paper also provides statistical information about performance of the model. Our objective is to create a survey aid for researchers to examine the latest trends of phishing attacks and contribute in building phishing detection models that yield greater accuracy.
Index Terms: Phishing, Legitimate, URL features, machine learning, phishing detection
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DOI:
10.17148/IJARCCE.2022.11552
