Improving malicious URLs detection via feature engineering: Linear and nonlinear space transformation methods

作者：

Highlights：

• Linear and non-linear space transformation methods for malicious URLs detection.

• 331622 URLs with 62 features were collected to validate the proposed methods.

• The proposed methods can improve the efficiency and performance of classifiers.

• A website was developed using the proposed methods to predict malicious URLs.

摘要

•Linear and non-linear space transformation methods for malicious URLs detection.•331622 URLs with 62 features were collected to validate the proposed methods.•The proposed methods can improve the efficiency and performance of classifiers.•A website was developed using the proposed methods to predict malicious URLs.

论文关键词：Feature engineering,Malicious URLs detection,Nyström method,Distance metric learning,Singular value decomposition

论文评审过程：Received 10 November 2017, Revised 1 December 2019, Accepted 12 January 2020, Available online 15 January 2020, Version of Record 23 January 2020.

论文官网地址：https://doi.org/10.1016/j.is.2020.101494