Detecting phishing pages using the relief feature selection and multiple classifiers

Seyyed Mohammad Javadi Moghaddam, Mohammad Golami · International Journal of Electronic Security and Digital Forensics · 2020

Website phishing is a deception in e-commerce, which attempts to steal user confidential information using similar websites. The classification technique is one of the common ways to detect phishing websites. According to high-volume main data, attribute reduction algorithms play an essential role. This paper presents an appropriate model based on the relief algorithm to reduce dimension. Moreover, the proposed approach uses multiple-classifiers to increase accuracy. The evaluated results show higher accuracy and superiority than conventional methods.

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