Intelligent Detection for Cyber Phishing Attacks using Fuzzy rule-Based Systems

Phoebe Barraclough, Gerhard Fehringer

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Cyber phishing attacks are increasing rapidly, causing the world economy monetary losses. Although various phishing detections have been proposed to prevent phishing, there is still a lack of accuracy such as false positives and false negatives causing inadequacy in online transactions. This study constructs a fuzzy rule model utilizing combined features based on a fuzzy inference system to tackle the foreseen inaccuracy in online transactions. The importance of the intelligent detection of cyber phishing is to discriminate emerging phishing websites with a higher accuracy. The experimental results achieved an excellent accuracy compared to the reported results in the field, which demonstrates the effectiveness of the fuzzy rule model and the feature-set. The findings indicate that the new approach can be used to discriminate between phishing and legitimate websites. This paper contributes by constructing a fuzzy rule model using a combined effective feature-set that has shown an excellent performance. Phishing deceptions evolve rapidly and should therefore be updated regularly to keep ahead with the changes.
Original languageEnglish
Pages (from-to)11001-11010
Number of pages10
JournalInternational Journal of Innovative Research in Computer and Communication Engineering
Issue number6
Publication statusPublished - 30 Jun 2017


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