A Node Differential Privacy-Based Method to Preserve Directed Graphs in Wireless Mobile Networks

Round 1

Reviewer 1 Report

The manuscript is well written, easy to follow and has adequate structure.

However, there are some minor changes, that must be made before publication. I am not going into technicalities but will focus mainly on methodological part of the manuscript.

Please rephrase some vague statements. E.g.: We provide some technologies to improve data utility.

Objectives are clear (propose a new method and validate it). However, I have slight problems understanding, how did you validate (in addition to performance) its correctness?

Can you explain your research method in more details in Introduction?

Please, in Conclusion, elaborate on objectives from introduction.

I would suggest mild restructuring of the manuscript: can you merge literature review with “preliminary knowledge”? On the other hand, it might be a good idea to split experimenting section from results.

I am completely missing “Threats of validity” section.

Language is grammatically on high level; however, I would suggest a mild proofread. “A, the…”-s can be improved, several plural/singular etc.:

...characteristics of the node is able to maintains the properties...

Related works

Preliminaries knowledge

...graph modifi-cation methods...

…

Author Response

please see the attachment

Author Response File: Author Response.docx

Reviewer 2 Report

- The introduction appears to lack a clear and concise structure. It jumps between discussing the benefits of 4G mobile wireless networks, the importance of individual privacy, graph modification methods, and differential privacy without a smooth transition or logical flow.  Also, the introduction spends a significant portion discussing the benefits and applications of 4G and future wireless networks, which might not be directly relevant to the specific research topic of preserving directed graphs in wireless mobile networks. It could benefit from focusing more on the specific problem and motivation behind the research .Although the introduction briefly mentions different graph modification methods, clustering, and uncertain graphs, it does not adequately connect them to the proposed method or explain how the proposed method builds upon or improves existing approaches. Providing more context and discussing the limitations of previous methods would strengthen the research's novelty and significance. To address these weaknesses, it would be helpful to revise the introduction by providing a clearer problem statement, linking the proposed method to existing research, and ensuring a logical flow of ideas. Additionally, stating specific research objectives and questions would enhance the clarity and focus of the introduction.

- Section 4:  While the section briefly mentions the importance of data utility, it does not provide a comprehensive analysis or discussion on how the proposed method balances privacy preservation and data utility. It would be valuable to address the trade-off between privacy and utility and provide insights into how the proposed method maintains the quality and usefulness of the data. Also, The section does not discuss the scalability of the proposed method, particularly in large-scale wireless mobile networks. As the size of the network and the amount of data increase, the computational and communication overheads may become significant. It is essential to consider the scalability of the method and any potential limitations or challenges that may arise in real-world deployments.

- Section5 : Although the section mentions a comparison with other methods from references [5] and [20], it does not provide sufficient details or explanations about these methods. It would be valuable to include a brief overview of the compared methods and discuss how the proposed method outperforms them. 
- Section 6: The section does not address potential limitations or drawbacks of the proposed method. It is essential to acknowledge and discuss any limitations, such as scalability issues, potential biases, or assumptions made in the methodology.

Author Response

please see the attachment

Author Response File: Author Response.docx

Round 2

Reviewer 2 Report

Authors have addressed my comments,