期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2019
卷号：7
期号：1
页码：359-371
DOI：10.15680/IJIRCCE.2019. 0701040
出版社：S&S Publications
摘要：The main objective of this system is to enhance the security mechanisms and avoiding the Phishing
attacks over web medium.Anti-phishing detection solutions employed in industry use blacklist-based approaches to
achieve low false-positive rates, but blacklist approaches utilizes website URLs only. This study analyses and combines
phishing emails and phishing web-forms in a single framework, which allows feature extraction and feature model
construction. The outcome should classify between phishing, suspicious, legitimate and detect emerging phishing
attacks accurately. The intelligent phishing security for online approach is based on machine learning techniques, using
Adaptive Neuro-Fuzzy Inference System and a combination sources from which features are extracted. An experiment
was performed using two-fold cross validation method to measure the system’s accuracy. The intelligent phishing
security approach achieved a higher accuracy. The finding indicates that the feature model from combined sources can
detect phishing websites with a higher accuracy. This project contributes to phishing field a combined feature which
sources in a single framework. The implication is that phishing attacks evolve rapidly. Therefore, regular updates and
being ahead of phishing strategy is the way forward.
