Title: Detecting phishing pages using the relief feature selection and multiple classifiers

Authors: Seyyed-Mohammad Javadi-Moghaddam; Mohammad Golami

Addresses: Department of Computer, Faculty of Engineering, Bozorgmehr University of Qaenat, Iran ' Department of Computer, Islamic Azad University, Birjand Branch, Iran

Abstract: 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.

Keywords: attribute reduction; combining classifications algorithm; phishing; relief algorithm.

DOI: 10.1504/IJESDF.2020.10027597

International Journal of Electronic Security and Digital Forensics, 2020 Vol.12 No.2, pp.229 - 242

Received: 06 Mar 2019
Accepted: 09 May 2019

Published online: 02 Apr 2020 *

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