Comparative analysis of machine learning classifiers for phishing detection

• Main Authors: Mohd Faizal, Ab Razak, Mohd Izham, Jaya, Ernawan, Ferda, Ahmad Firdaus, Zainal Abidin, Nugroho, Fajar Agung
• Format: Conference or Workshop Item
• Language: English; English
• Published: Institute of Electrical and Electronics Engineers Inc. 2022
• Subjects: QA75 Electronic computers. Computer science; QA76 Computer software; T Technology (General); TA Engineering (General). Civil engineering (General)
• Online Access: http://umpir.ump.edu.my/id/eprint/39337/1/Comparative%20analysis%20of%20machine%20learning%20classifiers%20for%20phishing%20detection.pdf; http://umpir.ump.edu.my/id/eprint/39337/2/Comparative%20analysis%20of%20machine%20learning%20classifiers%20for%20phishing%20detection_ABS.pdf; http://umpir.ump.edu.my/id/eprint/39337/; https://doi.org/10.1109/ICICoS56336.2022.9930531

In recent years, communication over the Internet has become the most effective media for leveraging social interactions during the COVID-19 pandemic. Nevertheless, the rapid increase use of digital platforms has led to a significant growth of Phishing Attacks. Phishing attacks are one of the most co...