Dear Editor

We would like to express great thanks to the reviewers for their valuable suggestions on our work. We have made the modifications as per the reviewer’s suggestions. The details of the modification and point to point response are given below.

Regards

Authors

<span class="underline">Additional Comments to Author(s)</span>

<span class="underline">Comment 1:</span> Overall, the researcher managed to achieve and prove the best supervised learning algorithm as the main objective of this article.

**Response:** Yes, we performed the performance analysis of various supervised learning algorithms on NSL-KDD dataset and shown the results with the performance metric called accuracy.

<span class="underline">Comment 2:</span> The article can be improved by considering the following aspects:

1.  Formatting - Please refer to the guideline as provided in the web site, especially for the references and citation (should APA style) and text (Times new Roman)  
    **<span class="underline">Response:</span>** The Journal’s paper template has been used to format the work. As suggested, references and citations were presented in APA style and text in Times New Roman font.

2.  Maybe the author could discuss the basic characteristics of the supervised learning algorithm, and then all the algorithms discussed should be provided with complete discussion details. You could consider helping the reader by providing a pseudo code/flowchart.

**<span class="underline">Response:</span>** We are thankful to the suggestion. We implemented six supervised learning algorithms such as K-NN, Linear Regression, Decision Tree, SVM, Random Forest, and Gaussian Naïve Bayes to check the accuracy of malicious traffic detection in NSL-KDD dataset. We have provided brief description of each method.

Figure 1 has been modified to show the clear methodology of the work. More explanation has been added in the sections Random Forest, SVM, and Decision Tree. Figure 4 and 5, equations (5) and (6) has been incorporated with related explanation. An example of decision tree is provided and its diagrammatic representation provided in Figure 5.

3.  Please check (some mistake at page 5) when referring to Figure/Table (Figure 1/Figure2) and spelling error at page 10 (hat)

> **<span class="underline">Response:</span>** Thanks for the observation. We have corrected the figure and table labels and numbering. Also cross verified with the text.

4.  Please check your conclusion because your statement is not reflected to your results, which is based on results the highest accuracy is random forest algorithm.

**<span class="underline">Response:</span>** Thanks for the observation. The suggestion has been incorporated and text has been verified.