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International Journal of Advanced Research in Computer and Communication Engineering A monthly Peer-reviewed & Refereed journal
ISSN Online 2278-1021ISSN Print 2319-5940Since 2012
IJARCCE adheres to the suggestive parameters outlined by the University Grants Commission (UGC) for peer-reviewed journals, upholding high standards of research quality, ethical publishing, and academic excellence.
← Back to VOLUME 12, ISSUE 7, JULY 2023

Phishing Websites Prediction based on Artificial Neural Network Technique

Tony Chhipne, Prof. Sushma Kushwaha

DOI: 10.17148/IJARCCE.2023.12747
Abstract- Phishing attacks have emerged as a significant threat to online security, targeting unsuspecting users to divulge sensitive information through fraudulent websites. To counter this threat, a proactive approach involving predictive techniques is crucial. This study presents a novel approach for predicting phishing websites using an Artificial Neural Network (ANN) technique. The proposed model leverages the inherent pattern recognition capabilities of ANNs to analyze a comprehensive set of features extracted from website URLs, content, and meta-information. A dataset comprising legitimate and phishing websites is used for training and evaluation. This paper presents phishing websites prediction based on artificial neural network technique. Index Terms- ANN, AI, Phishing Websites, Deep Learning.

How to Cite:

[1] Tony Chhipne, Prof. Sushma Kushwaha, “Phishing Websites Prediction based on Artificial Neural Network Technique,” International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2023.12747