A data reduction strategy and its application on scan and backscatter detection using rule-based classifiers

作者：

Highlights：

• A novel data reduction strategy is presented.

• Multi measure strategy is used to reduce the number of features.

• Training data is significantly reduced, without greatly affecting the IDS accuracy.

• Boost up the detection process speed.

• Does not require large computational resources to process a huge amount of data.

摘要

•A novel data reduction strategy is presented.•Multi measure strategy is used to reduce the number of features.•Training data is significantly reduced, without greatly affecting the IDS accuracy.•Boost up the detection process speed.•Does not require large computational resources to process a huge amount of data.

论文关键词：Data mining,Data reduction,Intrusion detection,Scan,Backscatter

论文评审过程：Received 1 August 2017, Revised 20 October 2017, Accepted 16 November 2017, Available online 21 November 2017, Version of Record 14 December 2017.

论文官网地址：https://doi.org/10.1016/j.eswa.2017.11.041