Phishing detection via identification of website identity
In this paper, we propose an anti-phishing method to protect Internet users from the phishing attacks. The scope of our study is on the Internet phishing, particularly focusing on the detection of phishing website. In order to do that, our proposed method will render a screenshot of the webpage and...
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my.unimas.ir.157672022-09-15T03:11:56Z http://ir.unimas.my/id/eprint/15767/ Phishing detection via identification of website identity Ee, Hung Chang Kang, Leng Chiew San, Nah Sze Wei, King Tiong T Technology (General) In this paper, we propose an anti-phishing method to protect Internet users from the phishing attacks. The scope of our study is on the Internet phishing, particularly focusing on the detection of phishing website. In order to do that, our proposed method will render a screenshot of the webpage and segment the region of interest, which consists of the website logo. Next, we will utilize Google image database to identify the website identity based on the segmented website logo. During the identification process, we employ the content-based image retrieval mechanism provided in Google Image Search engine to locate the most similar logo from Google image database. The returned results will reveal the real identity of the website. With the real identity, we can differentiate a phishing website from the legitimate website by assessing the domain name of the query website. The conducted experiments show promising results and our findings prove that we can effectively detect a phishing website when we manage to determine the real identity of a website 2013 Proceeding PeerReviewed text en http://ir.unimas.my/id/eprint/15767/1/Phishing%20detection%20via%20identification%20of%20website%20identity%20%28abstrak%29.pdf Ee, Hung Chang and Kang, Leng Chiew and San, Nah Sze and Wei, King Tiong (2013) Phishing detection via identification of website identity. In: International Conference on IT Convergence and Security (ICITCS), 2013, 16-18 Dec. 2013. DOI: 10.1109/ICITCS.2013.6717870 |
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T Technology (General) Ee, Hung Chang Kang, Leng Chiew San, Nah Sze Wei, King Tiong Phishing detection via identification of website identity |
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In this paper, we propose an anti-phishing method to protect Internet users from the phishing attacks. The scope of our study is on the Internet phishing, particularly focusing on the detection of phishing website. In order to do that, our proposed method will render a screenshot of the webpage and segment the region of interest, which consists of the website logo. Next, we will utilize Google image database to identify the website identity based on the segmented website logo. During the identification process, we employ the content-based image retrieval mechanism provided in Google Image Search engine to locate the most similar logo from Google image database. The returned results will reveal the real identity of the website. With the real identity, we can differentiate a phishing website from the legitimate website by assessing the domain name of the query website. The conducted experiments show promising results and our findings prove that we can effectively detect a phishing website when we manage to determine the real identity of a website |
format |
Proceeding |
author |
Ee, Hung Chang Kang, Leng Chiew San, Nah Sze Wei, King Tiong |
author_facet |
Ee, Hung Chang Kang, Leng Chiew San, Nah Sze Wei, King Tiong |
author_sort |
Ee, Hung Chang |
title |
Phishing detection via identification of website identity |
title_short |
Phishing detection via identification of website identity |
title_full |
Phishing detection via identification of website identity |
title_fullStr |
Phishing detection via identification of website identity |
title_full_unstemmed |
Phishing detection via identification of website identity |
title_sort |
phishing detection via identification of website identity |
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2013 |
url |
http://ir.unimas.my/id/eprint/15767/1/Phishing%20detection%20via%20identification%20of%20website%20identity%20%28abstrak%29.pdf http://ir.unimas.my/id/eprint/15767/ |
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