Next Article in Journal
A Novel Snow Leopard Optimization for High-Dimensional Feature Selection Problems
Next Article in Special Issue
Retrieval Integrity Verification and Multi-System Data Interoperability Mechanism of a Blockchain Oracle for Smart Healthcare with Internet of Things (IoT) Integration
Previous Article in Journal
Challenges of the Biopharmaceutical Industry in the Application of Prescriptive Maintenance in the Industry 4.0 Context: A Comprehensive Literature Review
Previous Article in Special Issue
An Efficient Privacy Protection Mechanism for Blockchain-Based Federated Learning System in UAV-MEC Networks
 
 
Article
Peer-Review Record

EADC: An Efficient Anonymous Data Collection Scheme with Blockchain in Internet of Things

Sensors 2024, 24(22), 7162; https://doi.org/10.3390/s24227162
by Zhiwei Si 1, Juhao Wang 1, Pengbiao Zhao 2, Xiaopei Wang 3 and Jingcheng  Song 1,*
Reviewer 1: Anonymous
Reviewer 2: Anonymous
Sensors 2024, 24(22), 7162; https://doi.org/10.3390/s24227162
Submission received: 11 October 2024 / Revised: 2 November 2024 / Accepted: 6 November 2024 / Published: 7 November 2024
  • Round 1
  • Reviewer 1 Report
  • Comments and Suggestions for Authors
  • The main idea of the paper is to introduce a new method called the efficient anonymous data collection (EADC) scheme. This method uses special math and encryption to keep data private and to improve data collection in the Internet of Things (IoT). It addresses important problems like user distrust and data manipulation, ensuring that data remains anonymous and is collected securely. As a result, it allows for detailed data gathering without compromising user privacy.
  • To enhance the paper, several suggestions can be made. First, conducting a comparative analysis with other data collection methods would help highlight the advantages of EADC more clearly. Additionally, including real-life examples or tests could demonstrate how well the method works in practice. Moreover, exploring how EADC performs in larger IoT networks under various conditions would provide insights into its scalability.
  • Furthermore, it would be beneficial to investigate potential weaknesses or attack vectors specific to the EADC scheme to strengthen its security measures. In addition, providing a more detailed explanation of the mathematical and encryption processes involved could help readers better understand the technical aspects. Moreover, considering ways for users to provide feedback could improve the system based on their experiences and concerns regarding privacy and data handling. Finally, formal methods can be used to verify the correctness of smart contracts and blockchain codes, which can help to prevent costly errors and security breaches. Therefore, it is important to discuss the use of formal methods in your paper. For this purpose, the authors may include the following interesting references (and others):

  • a. https://ieeexplore.ieee.org/document/9970534

    b. https://ieeexplore.ieee.org/document/8328737
  • Author Response
  • Please see the attachment.
  • Author Response File: Author Response.pdf
  • Reviewer 2 Report
  • Comments and Suggestions for Authors
  • The manuscript proposes an efficient anonymous data collection scheme called EADC, which is suitable for the Internet of Things environment. By combining matrix algorithms, homomorphic encryption technology, and smart contracts, the scheme effectively cuts off the direct connection between users and data and protects user privacy. At the same time, the overall efficiency of the system is improved by introducing a data grouping protocol. The article also conducts a detailed analysis of the execution efficiency, privacy protection and raw data collection of the EADC scheme, and compares it with existing schemes. Overall, the EADC scheme achieves fine-grained data collection while protecting user privacy, providing a new idea for privacy data collection in the Internet of Things. The manuscript is well organized and the proposed scheme provides valuable ideas with potential impact on related fields. However, I think there are some issues that need to be addressed in this paper.
  • 1. In Section 4, Algorithm 1, there seems to be some controversy regarding the format and description of the algorithm.
  • 2. In Table 2, the symbol “-” appears, but its meaning within the context of the table is not explained. Please provide a legend or footnote to clarify what this symbol represents in the comparison.
  • 3. In Figure 2, within the User Grouping section, it is observed that the Control Center (CC) receives Tr from User i, which should be Mr according to the context.
  • 4. In Section 4, Figure 2 under Case 2, the paper does not explain how the number of data collection group labels (k) is determined based on the number of users (n). Please provide an explanation.
  • 5. It is recommended that the authors carefully review and improve formatting and grammatical issues. The manuscript has some formatting and layout problems, such as missing spaces between words and paragraphs, as well as between parentheses and the main text.
  • Author Response
  • Please see the attachment.
  • Author Response File: Author Response.pdf
  • Round 2
  • Reviewer 1 Report
  • Comments and Suggestions for Authors
  • The authors considered my comments and suggestions. Good luck.
Back to TopTop