Detection of URL Based Phishing Websites Using Machine Learning in Django Framework
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Published:2022-03-31
Issue:3
Volume:10
Page:1151-1153
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ISSN:2321-9653
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Container-title:International Journal for Research in Applied Science and Engineering Technology
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language:
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Short-container-title:IJRASET
Author:
Kumari Khushboo,Jaison Feon
Abstract
Abstract: In this modern world, Phishing website detection is one of the most critical tasks in the world. In the recent times, a lot of people have suffered phishing attack due to phishing website. Machine Learning plays an important role in prediction of phishing website in the network. The proposed method predicts the URL based phishing websites based on features and also gives maximum accuracy to predict the result. This method uses uniform resource locator (URL) features to detect. It identified features that phishing site URLs contain. The proposed method takes those features for phishing detection. Security of the phishing detection website is also a major concern which is solved by providing administration who can manage the phishing detection website. Keywords: Phishing site, Machine learning, Legitimate, Prediction
Publisher
International Journal for Research in Applied Science and Engineering Technology (IJRASET)
Subject
General Earth and Planetary Sciences,General Environmental Science
Cited by
1 articles.
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