A new intrusion detection system based on Moth–Flame Optimizer algorithm

作者：

Highlights：

• A revision of feature selection methods for intrusion detection systems (IDS).

• A wrapper approach for IDSs based on moth–flame optimizer (MFO).

• Adoption of the cosine similarity measure to binarize the continuous MFO.

• IDS framework assessment against six feature selection methods.

摘要

•A revision of feature selection methods for intrusion detection systems (IDS).•A wrapper approach for IDSs based on moth–flame optimizer (MFO).•Adoption of the cosine similarity measure to binarize the continuous MFO.•IDS framework assessment against six feature selection methods.

论文关键词：Intrusion detection systems,Feature selection,Sigmoid function,Cosine similarity,Moth–Flame Optimization algorithm

论文评审过程：Received 11 April 2022, Revised 2 August 2022, Accepted 4 August 2022, Available online 10 August 2022, Version of Record 19 August 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.118439