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Article
Peer-Review Record

Quantifying Privacy Risks for Continuous Trait Data

Appl. Sci. 2022, 12(20), 10586; https://doi.org/10.3390/app122010586
by Muqing He 1, Deqing Zou 1,*, Weizhong Qiang 1, Shouhuai Xu 2, Wenbo Wu 3 and Hai Jin 4
Reviewer 1:
Reviewer 2:
Reviewer 3:
Reviewer 4:
Reviewer 5:
Appl. Sci. 2022, 12(20), 10586; https://doi.org/10.3390/app122010586
Submission received: 20 September 2022 / Revised: 14 October 2022 / Accepted: 17 October 2022 / Published: 20 October 2022

Round 1

Reviewer 1 Report

1.  In subsection (5.3.1.), page 12, authors must argue how the equations (7) and (8) were obtained, or indicate a bibliographic reference for their original form.

2. In page 15, Figure 7. Need more explanation about the Sensitivity with different r, z and p. In addition, on the same page, the equation (18) needs further clarification.

3. Generally the theoretical aspect of this research is weak and needs further development.

4. Future Scope is missing, please include it in concluding remarks.

Comments for author File: Comments.pdf

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 2 Report

Following comments can be addressed to improve quality of the paper as follows:

- Please define all acronyms at first such as QTL.

- Please describe your contributions as bullet form in Section 1.

- Section 2 can be merged to Section 3. Or. authors can extend Section 2 with some case studies and literature review.

- According to Figure 1, what is main novelty of Privacy-breaching model? Please explain with details.

- In Evaluation results, please compare the proposed method with other recent studies.

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 3 Report

In overall, the paper is well structured and each sections are well described. The results are supported by the findings. Also, the results are presented very well.

Author Response

Dear Reviewer 3:

Thank you for your comments concerning our manuscript entitled “Quantifying Privacy Risks for Continuous Trait Data” (applsci-1953289). We tried our best to improve the manuscript and made some changes in the manuscript. These changes will not influence the content and framework of the paper. And here we did not list the changes but marked them in orange in the revised paper. 

Thank you very much for your comments and suggestions.

       Yours sincerely,

       Muqing He

Reviewer 4 Report

Authors propose a scheme for systematically breaching genomic privacy, to quantify the probability of the privacy risk on continuous trait data. 

Paper is well written but requires major corrections to improve on its research quality.

My comments:

All acronyms should be defined at first mention

Rewrite contributions to knowledge, they look like summary of methods. What are the main contributions of the paper? Contributions should connect the studies implication, bringing up the strong points of the paper to justify its novelty.

Authors mention in the contributions section, the privacy implications of a trait dataset, but are silent on this issue throughout the paper. It will be nice to see a section on possible scientific implications of this work to enhance the interface of knowledge. 

I don't think bringing another or separate related works after discussion is proper. Please adhere to the journal's guidelines. I suggest everything about related works should come early to enable the identification of knowledge gaps. What should be seen in the discussion section should be a correlation of findings to literature.

Authors should check their definition in section 5.3 on pairwise combinations (with the three distributions) or make this definition clearer

Check the ordinate scale (metrics) of Fig. 4., not in percentage.

Some typo errors found. Authors should carefully screen the paper for typos. E.g., line 486 replace '...validity of major factors that summarized in the' with '...validity of major factors summarized in the'

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 5 Report

It is a well-developed article that proposes the working hypotheses and the contributions well. This is a very interesting field of application and both the methodologies used and their explanations and results are consistent and appropriate. The bibliography is pertinent and current and finally the conclusion is adequate and based on what has been done.

Author Response

Dear Reviewer 5:

Thank you for your comments concerning our manuscript entitled “Quantifying Privacy Risks for Continuous Trait Data” (applsci-1953289). We tried our best to improve the manuscript and made some changes in the manuscript. These changes will not influence the content and framework of the paper. And here we did not list the changes but marked them in orange in the revised paper. 

Thank you very much for your comments and suggestions.

       Yours sincerely,

Round 2

Reviewer 2 Report

This version is acceptable for publication 

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