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.
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Abstract
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
| Item Type: | Proceeding (Paper) |
|---|---|
| Additional Information: | Information, Communication and Creative Technology |
| Uncontrolled Keywords: | Google, Image segmentation, Security, Visualization, Image databases, Search engines, Accuracy, unimas, university, universiti, Borneo, Malaysia, Sarawak, Kuching, Samarahan, ipta, education, research, Universiti Malaysia Sarawak |
| Subjects: | T Technology > T Technology (General) |
| Divisions: | Academic Faculties, Institutes and Centres > Faculty of Computer Science and Information Technology Faculties, Institutes, Centres > Faculty of Computer Science and Information Technology Academic Faculties, Institutes and Centres > Faculty of Computer Science and Information Technology |
| Depositing User: | Saman |
| Date Deposited: | 31 Mar 2017 02:47 |
| Last Modified: | 15 Sep 2022 03:11 |
| URI: | http://ir.unimas.my/id/eprint/15767 |
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