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ISSN 2063-5346
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PHISHING LINK DETECTION USING MACHINE LEARNING

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Divyansh Sharma, Vishu Sharma, Yashashvi Dixit, Sonal Pahwa, Amit Kumar Saini
» doi: 10.48047/ecb/2023.12.si4.739

Abstract

In this paper safety and security for the user is provided by preventing them from accessing any harmful or suspicious link that may possibly be a phishing link while browsing the internet. As most of the financial and work-related activities have been moved to the internet, that makes us more exposed to cybercrime. Phishing attacks are one of the common threats to any internet user out there. In this the attacker exploits human vulnerability by tricking a person into revealing sensitive information through a URL or link that looks secured. A phisher can target both individuals and organizations, the main aim of phishers is to acquire a user's sensitive and critical information such as banking details, username and password, etc. To overcome this problem, we are using a Random Forest algorithm for detecting any phishing URL link based on the features of the URL, the extension will report and alert the user about the URL being a phishing link and not to be processed further. After testing various algorithms Random Forest Algorithm is applied to our dataset and create a user-friendly chrome based plugin also called as chrome extension

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