![]() ![]() These features are extracted from the URL, webpage properties and webpage behaviour using the incremental component-based system to present the resultant feature vector to the predictive model. ![]() The predictive model consists of Feature Selection Module which is used for the construction of an effective feature vector. In this work, an enhanced machine learning-based predictive model is proposed to improve the efficiency of anti-phishing schemes. Although Machine Learning approaches have achieved promising accuracy rate, the choice and the performance of the feature vector limit their effective detection. Despite the availability of myriads anti-phishing systems, phishing continues unabated due to inadequate detection of a zero-day attack, superfluous computational overhead and high false rates. Nowadays, many anti-phishing systems are being developed to identify phishing contents in online communication systems.
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June 2023
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