An Enhanced Trust Mechanism with Consensus-Based False Information Filtering Algorithm against Bad-Mouthing Attacks and False-Praise Attacks in WSNs

Round 1

Reviewer 1 Report

This paper proposes an enhanced trust mechanism with a consensus-based false information filtering algorithm (TM-CFIFA) that can effectively defend against bad-mouthing attacks and false-praise attacks.

Good point: the organization of the paper is good.

Major issues:

“Table 1 shows trust evaluation processes of a general reputation system and our trust mechanism (TM-CFIFA). ”, “Table 1. Experiment parameter setup” What is Table 1? Figure 4 cannot reflect the process of your description. And what is the different between (a) and (b)? What is the Algorithm 2 used for? It cannot locate in the paper and no description for it. It should add some description for the algorithms. Why you choose the values of the experimental parameters? You set initial trust value to 0.99, is it vulnerable to the Sybil attack? Language: there are some typos in the paper. Please check the whole paper. For example, “In general, a basic TM works in three phases as follows : (1) Observe its neighbor nodes’ behaviors...” --> Observes. “Node A forwards packets to node B, monitors whether node B normally forwards the received packets to node C...” It is not clear. “We conduct Experiment 1 by using experiment parameter shown in Table 1 as follows.” --> as follows

Author Response

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Author Response File: Author Response.pdf

Reviewer 2 Report

The authors study the problem of security in wireless sensor networks considering the bad-mouthing attacks and the false-praise attacks. The paper is overall well written and easy to follow. The mathematical analysis and the description of the algorithms provided in the manuscript are concrete and correct. The proposed approach is very interesting based on its holistic nature. However, there are some major comments that the authors should consider towards improving the quality of their manuscript. The major comments are listed as follows:

Some of the references are not necessary to be included to the paper, due to the fact that there exists more concrete literature to substitute those references, where the proposed concepts have already been presented. For example, references [18], [20] are very old and can be substituted by the following references: "On the Mitigation of Interference Imposed by Intruders in Passive RFID Networks." International Conference on Decision and Game Theory for Security. Springer, Cham, 2016, Reddy, Vijender Busi, et al. "A Similarity based Trust Model to Mitigate Badmouthing Attacks in Internet of Things (IoT)." 2019 IEEE 5th World Forum on Internet of Things (WF-IoT). IEEE, 2019. It is more valuable to the reader to refer to already applied theory and have the holistic view of the distributed denial of service attacks in this paper. The authors provide a very concrete analysis that the reviewer enjoyed to follow, however, the complexity analysis and the computational cost is missing from the manuscript. The authors should provide the theoretical complexity analysis of their algorithms and discuss how they will scale in large Internet of Things environments. The authors should thoroughly check the manuscript for grammar, typos and syntax errors. The authors should provide some comparative numerical results to other relevant research works from the recent literature in order to show the benefit of adopting their proposed framework. The presented numerical results show only the pure performance of the proposed framework, however without a comparative study to other approaches, the reader is not able to understand the benefits of the proposed framework.

The manuscript needs a minor revision before acceptance.

 

 

 

 

Author Response

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Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

Comments have been solved.

Writing can be further improved.