A New Scheme for Detecting Malicious Nodes in Vehicular Ad Hoc Networks Based on Monitoring Node Behavior

Round 1

Reviewer 1 Report

In general the paper is readable, the results in the paper are basically sound, but the paper needs to be improved in the following aspects:

- The paper structure should be improved. Section and subsection numbers need to be fixed. (E.g., Section 0? Section 3 appears two times.)

- It is mentioned in end of the introduction “Following that, VANET will be discussed in Section 3”, but this is not correct.

- References are needed to support some statements.

- What simulator was used?

- How many simulation runs were performed?

- The selection of numerical values for simulation input parameters should be presented and justified in terms of their relevance. 

- The simulator results were validated?

- Why analytical results weren't presented and validated against simulation results?

- Results should be compared with other research in this area discussed in the related work.

- More work is needed to assess the proof of concept of the proposed scheme. How will the proposed scheme perform in a different scenarios?

- Future work should be presented in order to motivate the conducted research.

- There are few writing errors that can be corrected by proofreading the paper. (E.g., Repeated text in page 3 lines 131-133. Chart captions must be corrected. “history .interaction”)

- Some references are incomplete, abbreviated, or not properly formatted.

Author Response

Thank you very much for the review of our manuscript. We sincerely appreciate all valuable comments and suggestions, which helped us to improve the quality of the article. We have read your comments carefully and tried our best to address them one by one. Please see the attached file.

Author Response File: Author Response.docx

Reviewer 2 Report

attached

Comments for author File: Comments.docx

Author Response

Thank you very much for the review of our manuscript. We sincerely appreciate all valuable comments and suggestions, which helped us to improve the quality of the article. We have read your comments carefully and tried our best to address them one by one. Please see the attachment. 

Author Response File: Author Response.docx

Reviewer 3 Report

The paper deals with a new method for the detection of malicious nodes in vehicular networks and the exclusion of the detected malicious nodes.

The proposal and the manuscript are interesting. The topic, the methodological innovation and the simulation study are relevant and consistent with the goals of the journal and the special issue. The paper is well written and clear, even if it could be imprpoved.

In general, the paper is suitable for publication after some changes. The innovative contribution of the paper with respect to the existing literature should be better highlighted and at least one application example should added to show the practical usefulness of the method.    

Minor changes:

• page 1, Introduction: this is section 1, hence, in the title, change “0” with “1”
• the acronyms in general should be defined in the text, the first time they are mentioned, and not in the abstract (e.g. VANET, RSU,…)
• page 4, first line from the top: replace “Where” with “where” (lower case)
• page 5: the sentence about the Central Limit Theorem is not correct. It is about the normal approximation of the sample mean distribution
• page 7, first line after equation 16: replace Tu with Ts

Author Response

Thank you very much for the review of our manuscript. We sincerely appreciate all valuable comments and suggestions, which helped us to improve the quality of the article. We have read your comments carefully and tried our best to address them one by one. Please see the attachment. 

Author Response File: Author Response.docx

Reviewer 4 Report

This paper proposes a malicious node detection scheme using the fuzzy logic model for evaluating the trust for each node. Simulations are used to validate the proposed technique. There are some comments as follows:

1) The motivations and technical contributions need to be further articulated. It is not clear what type of security is used for VANETs in the contribution part.

2) The signal power received may vary depending on channel conditions. How to determine the power signal received at the RSU in (1)? What is the distance between two consecutive RSU in practice?

3) Which encryption algorithm is used at each node? How can the probability be derived in (5)?

4) What if the referee nodes recommend malicious nodes to the RSU since the malicious nodes can also provide positive interactions?

5) What about the mobility model in this VANET considering security problems?

Finally, there are many grammar mistakes and typos, and the paper needs significant proofreading.

Author Response

Thank you very much for the review of our manuscript. We sincerely appreciate all valuable comments and suggestions, which helped us to improve the quality of the article. We have read your comments carefully and tried our best to address them one by one. Please see the attachment. 

Author Response File: Author Response.docx

Round 2

Reviewer 2 Report

Thanks for your efforts,

However, after rechecking the paper, comments have not done fully

Author Response

Paper S/N: futureinternet-1776247

Title of the Paper: A new scheme for Detecting Malicious nodes in vehicular ad hoc

networks based on Monitoring Nodes Behavior.

Author(s):

Dear Editor,

We would like to thank the reviewers for their diligent and thorough reading of this paper, as well as their intelligent comments and helpful suggestions, which helped to improve its quality. We are pleased to notify you that we have updated the manuscript in response to the reviewers' recommendations. We believe that the updated manuscript is in much better shape after incorporating the feedback. We appreciate the reviewer's forthright comments: we recognized that some crucial paragraphs of the original article lacked clarity, with ambiguities that led to reader misunderstandings. We have now added a new figure and several paragraphs to clarify the architecture of VANET. The updated version includes more related references. We have finally finished the editing and formatting process. This update, we believe, improves the manuscript's readability. The reviewer's comments are addressed in detail below.

We hope that these revisions improve the paper such that the reviewers now deem it worthy of publication in your esteemed journal. For the reviewers' convenience, we have followed their comments by our response in Times New Roman font. The uploaded a copy of the original manuscript marked with all the changes made during the revision process. The new text is highlighted.

Thank you

Ayoub Alsarhan

Reviewer 2

A new scheme for Detecting Malicious nodes in vehicular ad 2 hoc networks based on Monitoring Nodes Behaviour. The following are some comments regarding the paper:

Reply: Thank you very much for agreeing with us to the intention of this manuscript. We have read your comments carefully and tried our best to address them one by one, especially in terms of improving the presentation. We hope that the manuscript has been improved towards Future Internet standards after this revision.

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Comment: Change the English to third person perspective

Original Sentence: We evaluate the performance of our scheme by examining its ability to recognize untrustworthy nodes and evict malicious nodes from the network in order to increase the received ratio of accurate data and reduce the ratio of corrupted data

Change to: The Performance of our scheme was evaluated by examining its ability to recognize untrustworthy nodes and evict malicious nodes from the network in order to increase the received ratio of accurate data and reduce the ratio of corrupted data

Reply: Thank you so much for your comments that help us to improve our work significantly. The text has been revised as suggested. We went through the entire manuscript to eliminate grammatical mistakes.

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Comment: It is recommended to refer to the following paper for network and nodes in zonal architecture:

10. a) A.J. Moshayedi, A. S. Roy, L. Liao and S. Li, "Raspberry Pi SCADA Zonal based System for Agricultural Plant Monitoring," 2019 6th International Conference on Information Science and Control Engineering (ICISCE), 2019, pp. 427-433, doi: 10.1109/ICISCE48695.2019.00092.
11. b) A. J. . Moshayedi, A. S. . Roy, A. Kolahdooz, and Y. . Shuxin, “Deep Learning Application Pros And Cons Over Algorithm”, EAI Endorsed Trans AI Robotics, vol. 1, pp. 1–13, Feb. 2022
12. c) A. J. Moshayedi, S. K. Sambo and A. Kolahdooz, "Design And Development of Cost-Effective Exergames For Activity Incrementation," 2022 2nd International Conference on Consumer Electronics and Computer Engineering (ICCECE), 2022, pp. 133-137, doi: 10.1109/ICCECE54139.2022.9712844
13. d) A. Jahangir Moshayedi, G. Xu, L. Liao, and A. Kolahdooz, “Gentle Survey on MIR Industrial Service Robots: Review & Design,” J. Mod. Process. Manuf. Prod., vol. 10, no. 1, pp. 31–50, 2021.

e)A. J. Moshayedi, J. Li, and L. Liao, “Simulation study and PID Tune of Automated Guided Vehicles (AGV),” in 2021 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA), 2021, pp. 1–7.

2019. f) Gheisari, Mehdi, and Mehdi Esnaashari. "Data Storages in Wireless Sensor Networks to Deal With Disaster Management." Emergency and Disaster Management: Concepts, Methodologies, Tools, and Applications. IGI Global, 2019. 655-682.
2020. g) Gheisari, M., Alzubi, J., Zhang, X. et al. Correction to: A new algorithm for optimization of quality of service in peer to peer wireless mesh networks. Wireless Netw 25, 4445 (2019). https://doi.org/10.1007/s11276-019-02016-4.

Reply: We'd like to thank the reviewer for drawing our attention to these extremely intriguing works. Reference 1,2 have been added since they are close to our work. Please refer to the revised manuscript.

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Comment: Please check the full text carefully, avoid grammar or spelling mistakes

Reply: Thank you for your comment. The paper is checked. We have revised the WHOLE manuscript carefully. We tried to improve the presentation and to avoid any grammar or syntax error. Please refer to the revised manuscript.

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Comment: Authors are requested to make typesetting strictly according to the paper template on the conference website.

Reply: Thank you for your comment. We made typesetting according to the paper template on the journal website.  Please refer to the revised manuscript.

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Author Response File: Author Response.docx

Reviewer 4 Report

The authors have addressed my previous questions, I have no further comments.

Author Response

This paper proposes a malicious node detection scheme using the fuzzy logic model for evaluating the trust for each node. Simulations are used to validate the proposed technique. There are some comments as follows:

Comment: The motivations and technical contributions need to be further articulated. It is not clear what type of security is used for VANETs in the contribution part.

Reply: We thank the reviewer for raising this critical issue. We consider the challenge of recognizing and evicting malicious nodes in VANET based on trust level. Unlike most existing trust management techniques in the literature, node trustworthiness and maliciousness can be determined by looking at more than just RSU trust assessment; instead, we consider vehicle assessment and information correctness provided by a node.

The primary contribution of our scheme is to conduct a wide range of trust management assessments based on a variety of criteria. RSU undertakes a multi-trust management evaluation. These considerations include RSU evaluation, neighbors’ evaluation, and vehicle information accuracy. The subjective trust between vehicles is computed based on the local trust database of vehicles, and the suggested trust between vehicles is calculated based on the interaction information between the vehicles and neighbors. For the sake of assessing the degree of vehicle information, the notion of "information similarity" is employed. Meanwhile, we design algorithm to realize the calculation of vehicle hybrid trust value. The following paragraph was added to Section 1 to highlight the contribution.

Vehicles play a vital role in our scheme, which is based on data interaction.  Because our scheme not only uses the RSU to calculate and share the trust value, but also takes into account how vehicles calculate trust, this structure is flexible enough to solve the problem of low accuracy and real-time trust information that a vehicle may face when calculating trust.

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Comment: The signal power received may vary depending on channel conditions. How to determine the power signal received at the RSU in (1)? What is the distance between two consecutive RSU in practice?

Reply: We appreciate the reviewer's endorsement of our objective. The signal power was calculated like [1]. The distribution of RSU over the road is an interesting area, but it is beyond the scope of this work.

[1] A. Alsarhan and A. Agarwal, "Cluster-Based Spectrum Management Using Cognitive Radios in Wireless Mesh Network," 2009 Proceedings of 18th International Conference on Computer Communications and Networks, 2009, pp. 1-6, doi: 10.1109/ICCCN.2009.5235261.

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Comment: Which encryption algorithm is used at each node? How can the probability be derived in (5)?

Reply: We thank the reviewer for pointing this out.  We secure the safety messages sent between the different network nodes by encrypting them using the symmetric key cryptography.  Symmetric key cryptography has many advantages such as its straightforwardness, less memory occupation, less memory use, and less power utilization. Permitting only normal behaving nodes to participate in the VANET, hence increases the security and utilization of VANET’s resources.

In our work,  the Bernoulli distribution is used to model a single individual event (experiment) [1-2]  performed by a node in VANET.  The outcome of each event can have one of two possible outcomes : good or bad. The function in (5) is the probability density function for Bernoulli distribution. Deriving the function in (5) is beyond the scope of this work. The following paragraph was added to Section 2 to specify encryption algorithm that used to secure messages.

We secure the safety messages transmitted between network nodes by encrypting them with symmetric key cryptography.

1. Evans, M.; Hastings, N.; and Peacock, B. "Bernoulli Distribution." Ch. 4 in Statistical Distributions, 3rd ed. New York: Wiley, pp. 31-33, 2000.
2. Weisstein, Eric W. "Bernoulli Distribution." From MathWorld--A Wolfram Web Resource. https://mathworld.wolfram.com/BernoulliDistribution.html.

Comment: What if the referee nodes recommend malicious nodes to the RSU since the malicious nodes can also provide positive interactions?

Reply: We thank the reviewer for pointing this out. Our scheme takes into account the recommendations of all cluster members. One incorrect recommendation by a referee has no bearing on the ultimate trust value. Furthermore, our system evaluates the node's trustworthiness based on the data it provides. Unlike most existing trust management systems in the literature, node trustworthiness and maliciousness can be evaluated by considering vehicle assessment and information correctness offered by a node rather than merely RSU trust obtained over communication networks.

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Comment: What about the mobility model in this VANET considering security problems?

Reply: We would like to thank the reviewer for his/her valuable comments on the manuscript. In our work, vehicles are moving randomly and they change their speed arbitrarily. Vehicles select a direction randomly at each road intersection. Once the vehicle chooses a direction at an intersection, it moves straight until it arrives at the next intersection where it can change the direction. To clarify the mobility model in this VANET, the following paragraph was added to Section 2.

Vehicles in our work move at random and vary their speed at will. At each road intersection, vehicles choose a way at random. When a vehicle selects a direction at an intersection, it proceeds straight until it reaches the next intersection where it can change direction.

Definition 1. VANET can be represented as a network graph , where  is a collection of n nodes, comprising vehicles and RSUs, and  is the set of links.

Definition 2. In our model, the graph G is utilized to represent the city's roads.  is a graph made up of edge set  and vertex set . The road over intersections  and  is represented by the edge . The driver can drive directly from intersection  to intersection . We call a link, and a road is the undirected path that connects vertex  with vertex .

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Comment:  there are many grammar mistakes and typos, and the paper needs significant proofreading.

Reply: Thank you for your comment. The paper is checked. We have revised the WHOLE manuscript carefully. We tried to improve the presentation and to avoid any grammar or syntax error.

Author Response File: Author Response.docx