An improved ELM-based and data preprocessing integrated approach for phishing detection considering comprehensive features
作者：
Highlights：
• Define three types of features extracted from URLs, domains, etc.
• Exploit a method to balance the majority and minority class samples.
• Adopt an improved DAE-based method to reduce the dimension of the dataset.
• Boost the detection performance by using the improved ELM-based classifier.
• Do experiments to verify the feasibility and effectiveness of the proposed approach.
摘要
•Define three types of features extracted from URLs, domains, etc.•Exploit a method to balance the majority and minority class samples.•Adopt an improved DAE-based method to reduce the dimension of the dataset.•Boost the detection performance by using the improved ELM-based classifier.•Do experiments to verify the feasibility and effectiveness of the proposed approach.
论文关键词：Phishing detection,Extreme learning machine (ELM),ADASYN,SDAE,Dimension reduction,Non-inverse matrix
论文评审过程：Received 10 October 2019, Revised 15 July 2020, Accepted 7 August 2020, Available online 16 August 2020, Version of Record 1 September 2020.
论文官网地址：https://doi.org/10.1016/j.eswa.2020.113863
