Modified Firefly Optimization Algorithm-Based IDS for Nature-Inspired Cybersecurity

Round 1

Reviewer 1 Report

This paper proposes a new approach to cybersecurity that uses nature-inspired computing algorithms to analyze networks and detect suspicious activity quickly. The method is effective in reducing the number of suspicious nodes and increasing the turnaround time while focusing on proactive network protection through accurate health monitoring.

- I suggest the authors to not present equations in the related literature section. Here, the authors should present the context and past research useful to the description of their work. If there is any know theory used in their work, that should be explained in a following section.

- The authors should consider citing these works: doi.org/10.1016/j.ins.2021.01.062, doi.org/10.1007/978-3-030-52067-0_22

-  I would suggest the authors to first present some use case examples on the use of this algorithm and its benefits after the its explanation and modification, for example the two test cases they run in the experiments. This could be useful for the reader to understand what are the practical implication of the approach proposed and have a better understanding of the following experiments.

- Please, always use American English or British English. For example, sometimes you used "optimization", other times "optimisation".

- Figure 3b overlaps Figure 3a caption.

Author Response

Dear Reviewer,

We thank you for your efforts and feedback. The constructive comments and suggestions helped us to improve the manuscript's overall quality. We have tried our best to address all the comments and revised the manuscript accordingly.

Regards.

Author Response File: Author Response.pdf

Reviewer 2 Report

The author proposes an improved version of the firefly based on the event management schemes and the observation priority list based on a genetic evolution algorithm to monitor the network against intrusion. The paper seems original and interesting results are presented. This reviewer's suggestions, questions, and concerns for the paper are listed below:

1.      The paper is well written and organized, the topic is still very important, and the authors have done good contributions to state of the art in the paper. However, the authors should consider the following issue: 

2.      Any specific reason for choosing the firefly algorithm for comparison. Explore the outcome of your research with some other nature-inspired algorithms.

3.      Substantiate the ways to avoid getting stuck in a local minimum; the general statements about the problem are not enough, such as "while avoiding the issues of local maxima"

4.      A few of the references in Related Work are old. Authors need to refer to recent publications in this area, such as:

- Ganguli C, Shandilya SK, Nehrey M, Havryliuk M. Adaptive Artificial Bee Colony Algorithm for Nature-Inspired Cyber Defense. Systems. 2023 Jan;11(1):27.

- Nijim M, Goyal A, Mishra A, Hicks D. A Review of Nature-Inspired Artificial Intelligence and Machine Learning Methods for Cybersecurity Applications. Advances in Nature-Inspired Cyber Security and Resilience. 2022 Apr 27:109-18.

- Zaid M, Agarwal P. Intelligent Intrusion Detection System Optimized using Nature-Inspired Algorithms. In2022 1st International Conference on Informatics (ICI) 2022 Apr 14 (pp. 80-85). IEEE.

5.      The firefly algorithm has a control parameters.How did the authors select them?

6.      Initializing of the firefly algorithm is not clear. The starting search points of the algorithms are not clear

7.      Future work needs to be included in the conclusion section.

8.      The structure, format, and grammar of the paper need to be improved.

Author Response

Dear Reviewer,

We thank you for your efforts and feedback. The constructive comments and suggestions helped us to improve the manuscript's overall quality. We have tried our best to address all the comments and revised the manuscript accordingly.

Regards.

Author Response File: Author Response.pdf

Round 2

Reviewer 2 Report

The current version of the paper presents an expressive improvement as compared to the previous one. The authors provided acceptable answers to all questions and no more issues were detected in the current manuscript. Therefore, I recommend the acceptance of the paper.