Secure Information Sharing Approach for Internet of Vehicles Based on DAG-Enabled Blockchain
Round 1
Reviewer 1 Report
Following suggestions are encouraged to incorporate in your final version:
· Refine your Abstract.
· Include your results in the abstract.
· What is basic limitation in the existing system. And write down your strategy to handle it.
· Refine your conclusion section.
· Following research papers can be cited in your article:
o https://ieeexplore.ieee.org/abstract/document/9729883
o https://www.mdpi.com/1424-8220/22/12/4394
o https://ieeexplore.ieee.org/abstract/document/9183799
1. What is the main question addressed by the research?
Response: In this research article authors have proposed noval technique to handle the security related issues in vehicles network. Directed Acyclic Graph (DAG) and DDB-TSA Techniques are implemented.2. Do you consider the topic original or relevant in the field? Does it
address a specific gap in the field? Response: Yes, This topic is noval and have addressed all previous issues.
3. What does it add to the subject area compared with other published
material? Response: By this techniques security related issues are addressed, moreover, driving decision-based tip selection algorithm is makes this article more attractive and effective in the existing environment/techniques.
4. What specific improvements should the authors consider regarding the
methodology? What further controls should be considered? Response: methodology section has enough clarification about the proposed technique.
5. Are the conclusions consistent with the evidence and arguments presented
and do they address the main question posed? Response: Yes, conclusion is consistent and have good results.
6. Are the references appropriate? Response: Yes, The references is also appropriate.
7. Please include any additional comments on the tables and figures. Response: Minor changes are given in first review. Other then minor changes further changes are requried.
Author Response
Responses to Reviewers’ Comments on the Paper:
Secure Information Sharing Approach for Internet of Vehicles Based on DAG-Enabled Blockchain
Gangxin Du, Yangjie Cao, Jie Li and Yan Zhuang
We sincerely thank the editor and anonymous reviewers for their thorough reviews and constructive comments. The review comments are very helpful in further improving the quality of our paper. We have carefully revised the manuscript and addressed all the comments raised by the reviewers. Below are our point-to-point responses to the reviewers’ comments. The corresponding major changes to the original version of the paper are highlighted in yellow color in the revised manuscript.
Response to Reviewer 1
The authors would like to thank the reviewer for the valuable comments and constructive suggestions. Please kindly find beneath the detailed responses to the comments and the rationale for each modification to the manuscript as well.
Comment 1: Refine your Abstract and Include your results in the abstract.
Response 1: We thank the reviewer for the helpful suggestion. Below is the revised abstract.
Information sharing in vehicular networks has great potential for the future Internet of Vehicles (IoV). Vehicles and roadside units (RSUs) can exchange perceptual information and driving experience to enable intelligent transportation applications such as autonomous driving and road condition analysis. However, ensuring secure and efficient information sharing among vehicles is challenging. While traditional blockchain can guarantee the tamper-proof nature of shared information, it cannot be directly applied in large-scale vehicle networks due to its slow consensus process. Therefore, we propose an information sharing approach based on a directed acyclic graph (DAG), in which shared information is encapsulated into sites instead of blocks. We also propose a driving decision-based tip selection algorithm (DDB-TSA) and design a reputation-based rate control strategy (RBRCS) to ensure secure and efficient information sharing. Simulation results show that our approach reduces consensus latency, improves information sharing efficiency, and provides a more secure information sharing environment compared to existing DAG-enabled blockchain systems.
Comment 2: What is basic limitation in the existing system. And write down your strategy to handle it.
Response 2: We thank the reviewer for pointing this out. The basic limitation of existing systems is the need to ensure the integrity and security of the DAG topology. This also means that there are some attack methods in the DAG-enabled blockchain, such as parasitic chain attacks, which may threaten the security and integrity of transactions. Therefore, security analysis is conducted in Section 3.2 of the paper, and defense against parasitic chain attacks is proposed in Section 4.4.
Comment 3: Refine your conclusion section.
Response 3: We would like to thank the reviewer for the comment. Below is the revised conclusion.
This paper presents a secure and efficient information sharing scheme for vehicular networks by proposing a tip selection algorithm based on driving decisions using the DAG-enabled blockchain. The proposed algorithm is designed to address the time-sensitive requirements of a highly dynamic vehicular network environment by considering driving decisions to achieve fast consensus and increase the connection between shared information. Additionally, a reputation-based rate control strategy is introduced to mitigate parasitic chain attacks. Simulation results indicate that the proposed algorithm and strategy outperform existing work in terms of both security and efficiency. In future research, we plan to focus on reducing information redundancy to enhance consensus efficiency and further improve the scalability of the blockchain.
Comment 4: Following research papers can be cited in your article:
o https://ieeexplore.ieee.org/abstract/document/9729883
o https://www.mdpi.com/1424-8220/22/12/4394
o https://ieeexplore.ieee.org/abstract/document/9183799
Response 4: We thank the reviewer for the helpful suggestion. We have added these references in the appropriate places in the article. More specifically, we have added the following references.
[2] Hassan, M.A.; Javed, A.R.; Hassan, T.; Band, S.S.; Sitharthan, R.; Rizwan, M. Reinforcing Communication on the Internet of Aerial Vehicles. IEEE Transactions on Green Communications and Networking 2022, 6, 1288–1297.
[5] Rahman, S.A.; Tout, H.; Talhi, C.; Mourad, A. Internet of Things Intrusion Detection: Centralized, On-Device, or Federated Learning? IEEE Network 2020, 34, 310–317.
[7] Liu, W.; Watanabe, Y.; Shoji, Y. Vehicle-assisted data delivery in smart city: A deep learning approach. IEEE Transactions on Vehicular Technology 2020, 69, 13849–13860.
Once again, we would like to thank the reviewer for the constructive suggestions that helped improve the quality of this paper. We hope that we have been able to satisfactorily clarify all the points.
Author Response File: 
Author Response.pdf
Reviewer 2 Report
This paper describes the application of DAG-Enabled Blockchain to Secure Information Sharing Approach for the Internet of Vehicles. It provides valuable insights into the future era of the Internet of Vehicles. However, there are several things that could be improved.
(1) The most significant problem is the need for more clarity about the issues involved in the Internet of Vehicles.
When a vehicle is in motion, the processing is required on a per-second or per-millisecond basis. In addition, the environment surrounding the vehicle changes every second or millisecond. Is blockchain essential for this situation?
It is required to demonstrate the necessity with an easy-to-understand example. Also, the simulations in the latter half of the report should use that example.
Some of the simulations are in seconds. It is not easy to apply the result to a real car.
(2) There are also some things that could be improved with some details.
(a) In some of the papers in Related work, the author's name is the subject of the paper, but writing it this way makes it difficult to understand the point of that paper. It is better to explain the subject of the paper first.
(b) It needs to be clarified what the author wants to show in Figure 1, so an easy-to-understand explanation is necessary.
(c) In lines 217 and 238, you cite Equation 3. The equation number is correct?
(d) Chapter 4 discusses lightweight DAGs, but the definition of the proposed lightweight DAG needs to be clarified. It is necessary to show the difference between a normal DAG and the proposed method in a table.
(e) In line 329, "M is called particle deep and is large". "large" is not clear, so please explain clearly.
(f) What is the "h" in equation 7? In line 382, "Suppose the average time of each approval is h," but I cannot understand what h is.
(g) I see h in line 394; is it the same in equation 7?
(h) Line 404, equation 12 may be equation 14.
(i) Lines 472-476 need to be clarified for me. It should be a proper sentence.
(j) There is a simulation in section 5, but is not the number of cars, 18, too small?　In line 6, the authors mention that IoV is a large-scale network.
(k) It needs to be clarified what kind of simulation the authors would like to show.
(l) Table 3 should be written properly, not written as [24]. Why is it necessary to write so many algorithms?
(m) I need help understanding what section 5.2.1 means. Also, what is PD in Figure 3?
(n) I do not understand the meaning of lambda in line 507, so more explanation is needed.　
(o) In figure 4, what is CW?
(p) Can you explain the sentence "low genesis sites equal 10, and high genesis sites equal 1000" in line 516 in detail?
(q) Section 5.2.4 is easier to understand with a more careful explanation.
Author Response
Responses to Reviewers’ Comments on the Paper:
Secure Information Sharing Approach for Internet of Vehicles Based on DAG-Enabled Blockchain
Gangxin Du, Yangjie Cao, Jie Li and Yan Zhuang
We sincerely thank the editor and anonymous reviewers for their thorough reviews and constructive comments. The review comments are very helpful in further improving the quality of our paper. We have carefully revised the manuscript and addressed all the comments raised by the reviewers. Below are our point-to-point responses to the reviewers’ comments. The corresponding major changes to the original version of the paper are highlighted in yellow color in the revised manuscript.
Response to Reviewer 2
The authors would like to thank the reviewer for the valuable comments and constructive suggestions. Please kindly find beneath the detailed responses to the comments and the rationale for each modification to the manuscript as well.
Comment 1: When a vehicle is in motion, the processing is required on a per-second or per-millisecond basis. In addition, the environment surrounding the vehicle changes every second or millisecond. Is blockchain essential for this situation?
It is required to demonstrate the necessity with an easy-to-understand example. Also, the simulations in the latter half of the report should use that example.
Some of the simulations are in seconds. It is not easy to apply the result to a real car.
Response 1: We appreciate the reviewer for the valuable comment. For real-time processing of data in the Internet of Vehicles (IoV), such as data generated by sensors on a vehicle while in motion, blockchain may not be essential. In fact, blockchain technology may not be the most efficient option for real-time data processing due to its decentralized and consensus-based nature, which may result in slower transaction speeds. However, blockchain technology can still play a valuable role in the IoV ecosystem by providing secure and reliable storage and exchange of data when it is not necessary to process the data in real-time. For example, blockchain can be used to store data on the surrounding road conditions shared by vehicles, which can be securely accessed and verified by authorized parties. Furthermore, blockchain technology can also be used to establish trust among stakeholders in the IoV ecosystem, even if it is not used for real-time data processing. The decentralized and transparent nature of blockchain can provide a secure and trustworthy platform for data exchange and transactions, which can help to build trust among stakeholders, such as vehicle owners, manufacturers, and service providers. In summary, while blockchain technology may not be essential for real-time data processing in the Internet of Vehicles, it can still play an important role in ensuring secure and reliable data storage and exchange, as well as establishing trust among stakeholders in the IoV ecosystem.
Comment 2: In some of the papers in Related work, the author's name is the subject of the paper, but writing it this way makes it difficult to understand the point of that paper. It is better to explain the subject of the paper first.
Response 2: Thank you for your feedback. Our intention was to highlight the important contributions made by individual researchers in the field and the papers' relevance to our work. We believe that by including the authors' names as the subject of the paper, readers can easily recognize the authors' contributions and better understand the context of their work. Nonetheless, we will consider your feedback and make necessary adjustments to improve the clarity of our paper.
Comment 3: It needs to be clarified what the author wants to show in Figure 1, so an easy-to-understand explanation is necessary.
Response 3: We appreciate the reviewer for the valuable comment. We have added the following explanation to the beginning of Chapter 3.
Each vehicle belongs to a specific region, where it extracts information and generates sites. After the information is verified, it is added to the DAG blockchain and can be shared within the region or across regions.
Comment 4: In lines 217 and 238, you cite Equation 3. The equation number is correct?
Response 4: We appreciate the reviewer for raising this question. Yes, the equation number is correct.
Comment 5: Chapter 4 discusses lightweight DAGs, but the definition of the proposed lightweight DAG needs to be clarified. It is necessary to show the difference between a normal DAG and the proposed method in a table.
Response 5: We appreciate the reviewer for the valuable comment. There is not much difference between the normal DAG and the proposed method, except that the proposed method is more lightweight in handling conflicts. The modifications made are shown at the beginning of Chapter 4.
Comment 6: In line 329, "M is called particle deep and is large". "large" is not clear, so please explain clearly.
Response 6: We appreciate the reviewer for the valuable comment. As mentioned in "The angle"， the idea is to place the particle “deep” into the tangle so that it will not arrive at a tip straight away. However, the particle should not be placed “too deep” because it needs to find a tip in a reasonable time.
Comment 7: What is the "h" in equation 7? In line 382, "Suppose the average time of each approval is h," but I cannot understand what h is.
Response 7: We appreciate the reviewer for raising this question. Here, "h" refers to the average time required for a site to be appended to the DAG ledger.
Comment 8: I see h in line 394; is it the same in equation 7?
Response 8: We appreciate the reviewer for raising this question. Yes, they are the same.
Comment 9: Line 404, equation 12 may be equation 14.
Response 9: Thank you very much for your careful review of the paper. You are correct, and we have now corrected the formula numbering.
Comment 10: Lines 472-476 need to be clarified for me. It should be a proper sentence.
Response 10: We encountered an issue while exporting the file, and we apologize for that. After the modification, it can be displayed correctly at the end of Chapter 4.
Comment 11: There is a simulation in section 5, but is not the number of cars, 18, too small?　In line 6, the authors mention that IoV is a large-scale network.
Response 11: We appreciate the reviewer for the valuable comment. Here we referred to the experimental parameter settings in relevant papers (such as the references listed below) for the convenience of conducting experiments. The number of vehicles in the experiment does not conflict with the large-scale network of IoV.
Chai, H.; Leng, S.; Wu, F. Secure Knowledge Sharing in Internet of Vehicles: A DAG-Enabled Blockchain Framework. In 570 Proceedings of the ICC 2021-IEEE International Conference on Communications. IEEE, 2021, pp. 1–6.
Comment 12: It needs to be clarified what kind of simulation the authors would like to show.
Response 12: We appreciate the reviewer for the valuable comment. In terms of experiments, we first compare the proposed DDB-TSA and RBRCS with existing works, and then evaluate the proposed DAG-enabled information sharing scheme through simulation experiments. The simulation experiments include tip chosen delay, site confirmation delay, ledger convergence experiment, and parasitic chain attack defense experiment. The modifications made are shown at the beginning of Chapter 5.
Comment 13: Table 3 should be written properly, not written as [24]. Why is it necessary to write so many algorithms?
Response 13: We thank the reviewer for pointing this out. Here, we compare our proposed tip selection algorithm with those proposed in multiple articles to demonstrate that our algorithm has more advantages. Since the final displayed table is relatively long, we use reference numbers to indicate the corresponding algorithm used in each article.
Comment 14: I need help understanding what section 5.2.1 means. Also, what is PD in Figure 3?
Response 14: Thank you for raising this question. As part of evaluating the performance of DAG-enabled blockchain, tip chosen delay means the time takes for a new site to choose tips. That is, the time taken for a tip to join the DAG blockchain. The modifications made are shown at the beginning of Chapter 5.2.1.
PD stands for particle deep.
Comment 15: I do not understand the meaning of lambda in line 507, so more explanation is needed.
Response 15: We thank the reviewer for pointing this out. λrefers to the arrival rate of sites.
Comment 16: In figure 4, what is CW?
Response 16: We thank the reviewer for pointing this out. CW stands for cumulative weight.
Comment 17: Can you explain the sentence "low genesis sites equal 10, and high genesis sites equal 1000" in line 516 in detail?
Response 17: We thank the reviewer for pointing this out. We explained it in Section 5.2.3. To better demonstrate the convergence of the ledger, we provided two different initial values for the number of sites (e.g., low initial sites equal 10, and high initial sites equal 1000). The purpose is to show that regardless of the initial value of sites, the total number of sites in the ledger will eventually stabilize around a certain value, thus better proving the convergence of the ledger.
Comment 18: Section 5.2.4 is easier to understand with a more careful explanation.
Response 18: We appreciate the reviewer for the valuable comment. We provided a more detailed explanation in section 5.2.4. When attackers carry out parasitic chain attacks, they need to publish a large number of sites in a short period of time. Therefore, we analyzed the changes in the number of normal sites published by vehicles, the number of failed sites published, and the number of sites that require pledging assets to publish, under different probabilities of malicious behavior. A vehicle must pledge its reputation value when continuously releasing a site. We set the number of pledges per time to be twice that of the last time, and the mortgage reputation value is bound to the site. If the available reputation value of the vehicle is insufficient, the site cannot be published until the pledged reputation value is recovered. When the cumulative weight of a site reaches a certain threshold (for example, 150), the reputation value pledged on the site can be recovered, and two reputation values will be rewarded. As shown in Figure 6, the results show that the higher the probability of malicious behavior of the vehicles, the fewer normal sites they publish, making it difficult for them to publish a large number of sites in a short time and effectively resist parasitic chain attacks.
Once again, we would like to thank the reviewer for the constructive suggestions that helped improve the quality of this paper. We hope that we have been able to satisfactorily clarify all the points.
Author Response File: Author Response.pdf
Round 2
Reviewer 2 Report
I reviewed the response, and all questions were clarified. So I agree to accept this paper.
