Feature Selection with Weighted Ensemble Ranking for Improved Classification Performance on the CSE-CIC-IDS2018 Dataset

Round 1

Reviewer 1 Report

The paper proposes an ensemble method utilizing weight-based feature selection techniques to improve detection rates. It suggests that through this approach, it is possible to enhance the detection rate while reducing the number of features. However, there doesn't seem to be any notable contribution in the conventional category of feature selection. The paper should include a comparative analysis of the existing relevant studies to identify what distinguishes it. Additionally, the specific contributions of the paper should be clearly stated.

good. 

Author Response

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Author Response File: Author Response.docx

Reviewer 2 Report

The authors treat the feature selection with weighted ensemble ranking involved in a classification problem. The paper clearly shows performance improvement in a benchmark dataset after providing a big set of tests.

The paper answers positively to the questions required by this journal: the introduction provides sufficient background and include all relevant references; the cited references are relevant to the research; the research design is appropriate; the results are clearly presented; the conclusions are supported by the results.

I have only one comment: since the length of the paper will be big including the appendix with table of results, the authors are advised to save the appendix in a webpage and cite a link to that webpage in this paper, in the part where they discuss the results.

Author Response

Please see the attachment

Author Response File: Author Response.docx