Adebowale_et_al_2018.pdf (1.06 MB)
Intelligent web-phishing detection and protection scheme using integrated features of Images, frames and text
journal contribution
posted on 2023-08-30, 15:36 authored by Moruf A. Adebowale, Khin T. Lwin, Erika Sanchez, Mohammed Alamgir HossainA phishing attack is one of the most significant problems faced by online users because of its enormous effect on the online activities performed. In recent years, phishing attacks continue to escalate in fre- quency, severity and impact. Several solutions, using various methodologies, have been proposed in the literature to counter the web-phishing threats. Notwithstanding, the existing technology cannot detect the new phishing attacks accurately due to the insufficient integration of features of the text, image and frame in the evaluation process. The use of related features of images, frames and text of legitimate and non-legitimate websites and associated artificial intelligence algorithms to develop an integrated method to address these together. This paper presents an Adaptive Neuro-Fuzzy Inference System (ANFIS) based robust scheme using the integrated features of the text, images and frames for web-phishing detection and protection. The proposed solution achieves 98.3% accuracies. To our best knowledge, this is the first work that considers the best-integrated text, image and frame feature based solution for phishing detection scheme.
History
Refereed
- Yes
Volume
115Page range
300-313Publication title
Expert Systems with ApplicationsISSN
0957-4174External DOI
Publisher
ElsevierFile version
- Accepted version
Language
- eng
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Legacy posted date
2018-09-04Legacy creation date
2018-09-04Legacy Faculty/School/Department
ARCHIVED Faculty of Science & Technology (until September 2018)Usage metrics
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