Smart Attacks Learning Machine Advisor System for Protecting Smart Cities from Smart Threats
Round 1
Reviewer 1 Report
This study examines the notion of a smart-cities security IDS as effectively upgrading a typical IDS for smart city loT applications. They proposed SALMA as multi-level hybrid IDS for SDNs based on ELM that is used to devlope a smart attacks learning machine advisor system for protecting smart cities from smart threats. The system is based only on six flow features that are used in SDNs.
However, there are some suggestions to be revised to improve the quality of this paper as follows:
1. Abstract should be clear and check whether all the points mentioned in abstract are addressed in this manuscript. The abstract must summarize the performance evaluation results.
2. The paper contains only references before 2020; other years references also need to be added especially of 2021 and 2022.
3. A table should be added to summarized related work and state the approach and result achieved by other research in the literature.
4. Figure 1,2,5,6,7 are not clear.
5. Please cite Fig. 12, Fig. 13.
6. The variables in some equations must be defined.
7. English usage needs to be improved. Please carefully proofread the paper to get rid of typos and grammar mistakes.
8. References should follow the template. Please correct them all.
Author Response
Please see the attachment.
Author Response File: 
Author Response.docx
Reviewer 2 Report
The topic of the article fits the scope of the journal. The research topic will become more and more topical with the intensification of digitalization and the spread of the smart city concept. I consider it necessary to update the literature review of the paper, as little relevant literature has been processed in the last 2-3 years. The article contains a number of formal errors and inconsistencies (e.g.: bold in the abstract, devlope in the summary, different font sizes, etc.), please standardize this. The summary section is too general. It would be important to highlight the results achieved more clearly, as well as a more detailed comparison with the research results so far.
After making the requested modifications, I recommend the publication of the article.
Author Response
Please see the attachment.
Author Response File: Author Response.docx
Reviewer 3 Report
1. Author did not address problem clearly, existing work limitation did not well analyzed.
2. lack of literature review , author did not consider recently work.
3. implementation algorithm and step details are missing.
4. this paper very limited contribution already published many paper same idea , what is new in your paper author need detail explanation.
5. data set is too old.
6. result did not well discuss only very limited feature should be consider get high accuracy Proposed Approach (SALMA) 99.24 need more detail explanation
Author Response
Please see the attachment.
Author Response File: Author Response.docx
Round 2
Reviewer 1 Report
The comments have been addressed
Reviewer 2 Report
I accept the modified paper!
Reviewer 3 Report
All comments are well addresses.
This manuscript is a resubmission of an earlier submission. The following is a list of the peer review reports and author responses from that submission.
