Improve the effectiveness of machine learning models in detecting website phishing using morphological features in URL analysis
DOI:
https://doi.org/10.54654/isj.v2i22.1040Keywords:
website phishing detection, phishing URL, morphological featuresTóm tắt
With the proliferation of the Internet, the emergence of various threats has become increasingly prevalent, particularly the danger posed by phishing websites. These websites are designed with malicious content aimed at exploiting users who inadvertently access them. This method of attack represents a significant potential risk for users in cyberspace. The problem of detecting and eliminating phishing websites has garnered significant interest and research within the community. In this study, we propose a set of morphological features in URL path analysis, combined with machine learning methods, to detect phishing website URLs. Experimental evaluation with the UCI Repository dataset results have demonstrated the effectiveness of the proposed feature set in terms of all metrics (Accuracy, Precision, Recall, and F1 Score) compared to previous methods.
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