期刊名称：International Journal of Artificial Intelligence & Applications (IJAIA)
印刷版ISSN：0976-2191
电子版ISSN：0975-900X
出版年度：2019
卷号：10
期号：3
页码：1-8
DOI：10.5121/ijaia.2019.10304
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：Reducing the risk pose by phishers and other cybercriminals in the cyber space requires a robust and automatic means of detecting phishing websites, since the culprits are constantly coming up with new techniques of achieving their goals almost on daily basis. Phishers are constantly evolving the methods they used for luring user to revealing their sensitive information. Many methods have been proposed in past for phishing detection. But the quest for better solution is still on. This research covers the development of phishing website model based on different algorithms with different set of features in order to investigate the most significant features in the dataset.
关键词：Machine learning; Feature selection; Phishing; XGBoost; Random Forest (RF) and Probabilistic NeuralNetwork (PNN)
