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International Advanced Research Journal in Science, Engineering and Technology
International Advanced Research Journal in Science, Engineering and Technology A Monthly Peer-Reviewed Multidisciplinary Journal
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← Back to VOLUME 8, ISSUE 6, JUNE 2021

Detection of Website Phishing Attack Based on Deep Learning

Deepali B.Vaidya, Poonam R. Dholi

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Abstract: Phishing sites which expect to take the users private data by attracting them to visit a fake website page that resembles a honest to goodness one is another type of criminal acts through the internet and its one amongst the particularly considerations toward varied areas as well as e-managing an account. Phishing website detection is really an unpredictable and component issue including numerous components and criteria that aren't stable. Proposed an intelligent model for detecting phishing web pages based on Deep Learning. Types of web content are completely different in terms of their features. Hence, we have to use a selected web page features set to avoid phishing attacks. We proposed a model which is based on Deep Learning techniques to detect phishing websites. We have done analysis of three models of algorithms and we have suggested some new rules to have efficient feature classification.

Keywords: Phishing websites, Machine Learning, SVM, NB, ELM.

How to Cite:

[1] Deepali B.Vaidya, Poonam R. Dholi, “Detection of Website Phishing Attack Based on Deep Learning,” International Advanced Research Journal in Science, Engineering and Technology (IARJSET), DOI: 10.17148/IARJSET.2021.86143

Creative Commons License This work is licensed under a Creative Commons Attribution 4.0 International License.