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The article is ready for publication since the authors have completed all needed corrections.
[# PeerJ Staff Note - this decision was reviewed and approved by Sedat Akleylek, a PeerJ Computer Science Section Editor covering this Section #]
Please revise the article in order to make the originality clear to the readers.
Τhe authors improved the paper considerably and responded satisfactorily to the reviewers' comments.
No comment
No comment
Τhe authors improved the paper considerably and responded satisfactorily to the reviewers' comments.
The paper is well structured. The analysis of the findings is very interesting. Literature reference is relevant and covers the topic
The proposed scheme has certainly been used in the right way and the authors in the revised manuscript, try to clarify the experiment results.
In the performance evaluation, the authors need more effort to achieve novelty.
The main technical drawback in the revised manuscript even now is the lack of originality and novelty.
Please address all comments and submit a response letter detailing all corrections made.
[# PeerJ Staff Note: Please ensure that all review comments are addressed in a rebuttal letter and any edits or clarifications mentioned in the letter are also inserted into the revised manuscript where appropriate. It is a common mistake to address reviewer questions in the rebuttal letter but not in the revised manuscript. If a reviewer raised a question then your readers will probably have the same question so you should ensure that the manuscript can stand alone without the rebuttal letter. Directions on how to prepare a rebuttal letter can be found at: https://peerj.com/benefits/academic-rebuttal-letters/ #]
No comment.
The proposed proposed (θ*, k)-utility algorithm, independently generalizes the QI values to create less distance ECs for any size of k, which results in low utility loss as compared to its counterparts. However, the authors need to better explain the contribution of this algorithm except of the transformed 1:M microdata T into 1:1 microdata. They also need to focus on the equation (5). How the input value (2k) is selected to θ -Sensitive k-Anonymity algorithm?
Last, it is known that the θ-Sensitivity, is the product of variance (σ^2) and
Observation 1 (μ). Τhe symbolism (θ*) in the proposed algorithm indicates some optimization in the parameter (θ)? Τhis symbolism needs clarification.
The experimental results of the proposed (θ*, k)-utility technique for 1:M
dataset outforms in terms of utility, privacy, and computational efficiency. Ηowever some clarifications are needed:
- In Figure 8, the privacy loss is zero for all values (k)? This needs clarification.
The section about the "Future Work" must be extended. For example, would it be helpful to use cluster-based anonymization algorithms to construct the hierarchical structure of the sensitive attributes of Figure 2?
The paper is well structured. The analysis of the findings is very interesting. Literature reference is relevant and covers the topics but the main contributions of the paper are not sufficient to justify another paper on top of what already exists in the literature
As a concept, it is well designed. The proposed scheme has certainly been used in the right way but simulations results presented in this paper need more work to from being comprehensive.
There is not much novelty and contribution in the performance evaluation.
The subject of this paper is in the right direction on a very important issue of privacy and anonymized data, but more effort is needed to become competitive. The main technical drawback is the lack of originality and novelty in the paper.
This paper addresses the problem of anonymizing the 1:M microdata by significantly improving the
utility of anonymized release. The manuscript has merit, but the following comments should be answered carefully should I recommend publication of this work.
1. A detailed description must be included in the paper that emphasizes the main pros and cons of the authors’ proposal with regard to the state of the art.
2. The authors must extend the explanation of how the proposed technique can be extended to cover a wider scientific area without reducing the main points that are currently described.
3. I think that if the authors wish this paper is well considered by experts in the cyber security communities, more attention should be devoted to discussing the application scenario. I suggest simplifying it or better explain with realistic examples.
The authors should probably provide more information about the proposed architecture. This is a major issue of the paper of how the authors have chosen this specific architecture for the proposed processing method, how it emerged and why the proposed architecture is the optimal solution.
A major issue with the paper is the explanation of the results, which are presented casually and without thorough analysis.
The figures are small and apparently of low resolution. If the authors consider that it provides important information, they should definitely enlarge it to be clear and legible.
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