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Peer-Review Record

Privacy Preserving Data Publishing with Multiple Sensitive Attributes based on Overlapped Slicing

Information 2019, 10(12), 362; https://doi.org/10.3390/info10120362
by Widodo 1,2, Eko Kuswardono Budiardjo 1 and Wahyu Catur Wibowo 1,*
Reviewer 1: Anonymous
Reviewer 2: Anonymous
Information 2019, 10(12), 362; https://doi.org/10.3390/info10120362
Submission received: 15 October 2019 / Revised: 12 November 2019 / Accepted: 13 November 2019 / Published: 21 November 2019

Round 1

Reviewer 1 Report

The article “Privacy Preserving Data Publishing with Multiple Sensitive Attributes based on Overlapped Slicing” addresses the privacy issue for multiple sensitive attributes. The authors propose overlapped slicing approach for privacy preserving data publishing. This paper is not applicable for publishing at its current state. This paper needs to improve significantly in writing and method development. Some comments: • The novelty is week for somewhat and there is no significant contribution. • Authors should explain the mathematical model of the proposed method and should provide an analysis regarding the logical correctness of the key algorithms, and the properties that the paper claims should be proved or analyzed. • Author should cite more recent work in this field. • Authors should include privacy analysis between privacy and utility. • Differential privacy ensures the user privacy in the published dataset. They did not provide any relation of their work with the differential privacy. • Authors should compare their work with recent state of the art techniques.

Author Response

Dear reviewer 1, please see the attachment.

Author Response File: Author Response.docx

Reviewer 2 Report

What is micro data? The authors should clearly define it. There is a lack of related work. For example, Secure data outsourcing with adversarial data dependency constraints。  In the experiments, the authors should compare the data utility with other approaches to prove its advantage. Also, the experiments are only performed on a single dataset, which is also outdated. Can the approach be applied on datasets where some numerical attributes have thousands of unique values?

Author Response

Dear reviewer 2, please see the attachment.

Author Response File: Author Response.docx

Round 2

Reviewer 1 Report

There are some typos in the manuscript, such as in citation number 22 "Hassan" will be "Hasan". Authors should carefully review the paper before final draft.

Author Response

Dear Reviewer 1,

We fixed some typos in our manuscript as you ask for. Our manuscript definitely free from typos now. Term like 'anatomisation' is term created by other author in previous works. therefore it is considered as a new term and correct. We think we do not need an attachment file to explain our response, it is sufficient to submit the revised article.

Thank you for reviewing our article.

Kindly regards,

Authors

Reviewer 2 Report

The authors have successfully addressed my comments.

Author Response

Dear Reviewer 2,

Thank you for reviewing our article. Hopefully, it will be accepted in Information journal.

Kindly regards,

Authors

 

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