Nisreen Innab1, Ahmed Abdelgader Fadol Osman2, Mohammed Awad Mohammed Ataelfadiel2, Marwan Abu-Zanona3,*, Bassam Mohammad Elzaghmouri4, Farah H. Zawaideh5, Mouiad Fadeil Alawneh6
CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 1325-1345, 2024, DOI:10.32604/cmc.2024.051778
- 18 July 2024
Abstract Phishing, an Internet fraud where individuals are deceived into revealing critical personal and account information, poses a significant risk to both consumers and web-based institutions. Data indicates a persistent rise in phishing attacks. Moreover, these fraudulent schemes are progressively becoming more intricate, thereby rendering them more challenging to identify. Hence, it is imperative to utilize sophisticated algorithms to address this issue. Machine learning is a highly effective approach for identifying and uncovering these harmful behaviors. Machine learning (ML) approaches can identify common characteristics in most phishing assaults. In this paper, we propose an ensemble approach… More >