文章基本信息

标题：PhishFind - An Enhanced Adaptive Neuro-Fuzzy Inference System Phishing Detection over Fog Networks
本地全文：下载
作者：B.Seetha ; V.Ilayaraja
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.
关键词：Phishing websites; Neuro;fuzzy network; Neural network; Fuzzy; Fog computing; Cloud computing;