Malware Analysis in IoT & Android Systems with Defensive Mechanism
, Aruna Yadav 2, Himansu Sekhar Pattanayak 2, Ravindra Kumar 3, Arfat Ahmad Khan 4, Mohd Anul Haq 5,*, Ahmed Alhussen 6,* and Sultan Alharby 5
Round 1
Reviewer 1 Report
This article classifies different attacks in IoT and Android devices, mitigation strategies proposed by different researchers in past. This article emphasizes the role of the developer in secure application design. This article attempts to provide a relative analysis of several malware detection methods in the different environments of attacks. This study has expanded awareness of some application hardening strategies applicable for IoT devices and Android applications & devices. This study will help the domain experts and researchers to gain knowledge of IoT systems and Android systems from a security point of view and provide some insights on how to design more efficient, robust, and comprehensive solutions.
This paper contains a new approach for gain knowledge of IoT systems and Android systems.
This paper is well-written but need few improvements. This paper should be revised according to given suggestions.
1. Please revise Abstract to highlight main contribution.
2. Please add list objectives and limitations in introduction.
3. The literature review presented here is highly insufficient and generalized. Please improve it using recent papers. Please study new fuzzy models: linear Diophantine fuzzy sets, spherical linear Diophantine fuzzy sets, circular fuzzy set, etc.
4. Please add a comparison analysis of proposed work with existing techniques.
5. Some equations and formulas are not properly elaborated.
6. Few variables are not defined. Please correct it. Please use simple symbols.
7. Please check, equations numbering, labels and refs, captions, etc.
Author Response
Dear Reviewer:
We were pleased to have an opportunity to revise our paper now entitled, “Multi-class Pixel Certainty Active Learning Model for Remote Sensing Applications”. In revising the paper, we have carefully considered your comments and suggestions, as well as those of the reviewers. As instructed, we have attempted to succinctly explain changes made in reaction to all comments. We reply to each comment in a point-by-point fashion.
Author Response File: 
Author Response.pdf
Reviewer 2 Report
Dear authors, the comments are a critical review of the presented paper and should not be seen as directed to you or to your hard work.
1. There are several errors where words appear together. For example, lines 75, 79, 81 and many other lines.
2. Careful review should be made of the use of acronyms. For example, IIoT is used before its definition.
3. The work presents an exhaustive discussion about the most varied types of attacks. However, in terms of conclusions, there does not seem to be a support between the suggestions and the description of the typologies of attacks. I believe that this part could be improved so that developers properly understand the implications of adopting the eight recommendations. Also questionable is the originality of recommendations such as, "A strong suggestion is given for developers ... two step or multi step verification, strong encryption algorithm."
Author Response
Dear Reviewer:
We were pleased to have an opportunity to revise our paper now entitled, “Multi-class Pixel Certainty Active Learning Model for Remote Sensing Applications”. In revising the paper, we have carefully considered your comments and suggestions, as well as those of the reviewers. As instructed, we have attempted to succinctly explain changes made in reaction to all comments. We reply to each comment in a point-by-point fashion.
Author Response File: Author Response.pdf
Reviewer 3 Report
I have reviewed the manuscript "Malware Analysis in IoT & Android System with Defensive Mechanism". The topic addressed in the manuscript is potentially interesting and the manuscript contains some practical meaning, however, there are some issues which should be addressed by the authors:
1. The readability and presentation of the study should be further improved.
2. All figures should be improved to higher resolution.
3. The "Introduction" section of the manuscript is not well organized. The "Introduction" section can be made much more impressive by highlighting your contributions.
4. The authors should clearly emphasize the contribution of the study. Please note that the up-to-date of references will contribute to the up-to-date of your manuscript. The studies can be used to explain the method in the study or to indicate the contribution in "Introduction" section.
5. Conclusion section should be rearranged. Taking advantage of these results, striking suggestions can be made for future studies.
This study may be proposed for publication if it is addressed in the specified problems.
Author Response
Dear Reviewer:
We were pleased to have an opportunity to revise our paper now entitled, “Multi-class Pixel Certainty Active Learning Model for Remote Sensing Applications”. In revising the paper, we have carefully considered your comments and suggestions, as well as those of the reviewers. As instructed, we have attempted to succinctly explain changes made in reaction to all comments. We reply to each comment in a point-by-point fashion.
Author Response File: Author Response.pdf
Round 2
Reviewer 3 Report
They have covered the literature in depth. The projection for future work is very useful for the researchers to work in this topic. In my opinion, this study can be proposed for the publication.
