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DOI: 10.14569/IJACSA.2017.080601
PDF

Intelligent Security for Phishing Online using Adaptive Neuro Fuzzy Systems

Author 1: G. Fehringer
Author 2: P. A. Barraclough

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 8 Issue 6, 2017.

  • Abstract and Keywords
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Abstract: 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 paper 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.

Keywords: Phishing websites; fuzzy models; feature model; intelligent detection; neuro fuzzy; fuzzy inference system

G. Fehringer and P. A. Barraclough, “Intelligent Security for Phishing Online using Adaptive Neuro Fuzzy Systems” International Journal of Advanced Computer Science and Applications(IJACSA), 8(6), 2017. http://dx.doi.org/10.14569/IJACSA.2017.080601

@article{Fehringer2017,
title = {Intelligent Security for Phishing Online using Adaptive Neuro Fuzzy Systems},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2017.080601},
url = {http://dx.doi.org/10.14569/IJACSA.2017.080601},
year = {2017},
publisher = {The Science and Information Organization},
volume = {8},
number = {6},
author = {G. Fehringer and P. A. Barraclough}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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