Phishing Identification Using a Novel Non-Rule Neuro-Fuzzy Model

This paper presents a novel approach to overcome the difficulty and complexity in identifying phishing sites. Neural networks and fuzzy systems can be combined to join its advantages and to cure its individual illness. This paper proposed a new neuro-fuzzy model without using rule sets for phishing...

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Bibliographic Details
Published in:International journal of computer science and information security 2016-04, Vol.14 (4), p.8-8
Main Authors: Nguyen, Luong Anh Tuan, Nguyen, Huu Khuong
Format: Article
Language:English
Subjects:
Artificial neural networks
Computer information security
Cures
Cybercrime
Fuzzy logic
Mathematical analysis
Mathematical models
Neural networks
Phishing
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Summary:This paper presents a novel approach to overcome the difficulty and complexity in identifying phishing sites. Neural networks and fuzzy systems can be combined to join its advantages and to cure its individual illness. This paper proposed a new neuro-fuzzy model without using rule sets for phishing identification. Specifically, the proposed technique calculates the value of heuristics from membership functions. Then, the weights are trained by neural network. The proposed technique is evaluated with the datasets of 22,000 phishing sites and 10,000 legitimate sites. The results show that the proposed technique can identify with an accuracy identification rate of above 99%.
ISSN:1947-5500