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

Barraclough, Phoebe and Fehringer, Gerhard (2017) Intelligent Detection for Cyber Phishing Attacks using Fuzzy rule-Based Systems. International Journal of Innovative Research in Computer and Communication Engineering, 5 (6). pp. 11001-11010. ISSN 2320-9798

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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.

Item Type: Article
Uncontrolled Keywords: Phishing detection; Cyber phishing attack; Fuzzy rule-base; Phishing websites; Intelligent detection
Subjects: G400 Computer Science
G500 Information Systems
G600 Software Engineering
G700 Artificial Intelligence
G900 Others in Mathematical and Computing Sciences
H600 Electronic and Electrical Engineering
J900 Others in Technology
X900 Others in Education
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Related URLs:
Depositing User: Phoebe Barraclough
Date Deposited: 09 May 2018 10:15
Last Modified: 01 Aug 2021 09:24

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