Sensor-Based Entropy Source Analysis and Validation for Use in IoT Environments
Round 1
Reviewer 1 Report
- Results: Recommend to be Major revisions
This paper proposes and validates a source of entropy based on randomness collected from sensors used for motion detection. The proposed solution is analyzed in terms of resistance to multiple types of attacks. Following an analysis of the influence of sensor characteristics and settings on the entropy rate, then, authors obtain a maximum entropy value of 0.63 per bit, and a throughput of 3.12 Kb/s, even in the case where no motion is applied on the sensors. The results show that a stable and resistant entropy source can be built based on the data obtained from the sensors. The assessment of the proposed entropy source also achieves a higher complexity than previous studies, in terms of the variety of approached situations, and the types of the performed experiments.
It is with minor merits for Electronics, however, it requires some major revisions.
Firstly, for abstract section, it should be refined to clearly indicate what authors had done within 150 words.
Secondly, for Sections 1 and 2, authors should provide the comments of the cited papers after introducing each relevant work. What readers require is, by convinced literature review, to understand the clear thinking/consideration why the proposed approach can reach more convinced results. This is the very contribution from authors. In addition, authors also should provide more sufficient critical literature review to indicate the drawbacks of existed approaches, then, well define the main stream of research direction, how did those previous studies perform? Employ which methodologies? Which problem still requires to be solved? Why is the proposed approach suitable to be used to solve the critical problem? We need more convinced literature reviews to indicate clearly the state-of-the-art development. The introduction section is too simple and sometimes naïve.
For Sections 3 and 4, authors should introduce their proposed research framework more effective, i.e., some essential brief explanation vis-à-vis the text with a total research flowchart or framework diagram for each proposed algorithm to indicate how these employed models are working to receive the experimental results. It is difficult to understand how the proposed approaches are working.
For Section 5, authors should use more alternative models as the benchmarking models, authors should also conduct some statistical test to ensure the superiority of the proposed approach, i.e., how could authors ensure that their results are superior to others only based on Table 11? Meanwhile, authors also have to provide some insight discussion of the results. Authors can refer the following references for conducting statistical test.
Support vector regression model based on empirical mode decomposition and auto regression for electric load forecasting. Energies, 2013, 6(4), 1887-1901.
Electric load forecasting based on LSSVM with fuzzy time series and global harmony search algorithm. Energies, 2016, 9(2), 70.
Chaos cloud quantum bat hybrid optimization algorithm. Nonlinear Dynamics, 2021, 103(1), 1167-1193.
Author Response
Please see the attachment.
Author Response File: 
Author Response.pdf
Reviewer 2 Report
This article has very well-conducted introduction and experiments, and provides solid and convincing results. One issue that the authors should address is the grammar mistakes. It's suggested to improve the writing and fix typos and wrong capitalization, such as "genrated", "experiment X". The texts in Figure 3-4 are also overlapped. Please fix.
Another major concern is about the novelty. I agree that the article designs and performs comprehensive and sufficient experiments to the proposed entropy collection method. However, the method itself is not novel and has appeared in a bunch of articles. Besides the experiment design, what are the contributions of the article? Is there anything new in your entropy source model? While other articles also pick the three (and more) sensors used in the article: if they also conducted the same experiments, would their articles be the same or similar with yours? Please list your contributions explicitly. If the major novelty is in the experiment design, please state it and perhaps also reflect is in the title and abstract.
Author Response
Please see the attachment.
Author Response File: Author Response.pdf
Round 2
Reviewer 1 Report
Authors have completely addressed all my concerns.
