# A Systematic Review of Radio Frequency Threats in IoMT
## 4 Conclusions and Future Works  
The PRISMA-based search and systematic literature review identify the research gap in radio frequency spectrum threats in the hospital ecosystem. The potential gap is well analyzed, and the results are visualized. This research paper will be relevant to the IoT, IoMT, and medical readers, as this will open a new dimension for physicians and healthcare researchers in spectrum-level threats in machine implantable communication systems. Examples: deep brain stimulators, implantable cardioverter-defibrillator, cardiac stents, implantable insulin pumps, interocular lenses, and pacemakers.  
Time difference of arrival (TDOA)-based IoMT field experimentation will be used in our future research to validate the defensive framework. The framework will guide healthcare stakeholders while implementing corporate cybersecurity strategies.  
Eventually, further analysis will answer why and how sniffing attacks occur and how they can be identified and mitigated. We will use the design science research methodology to validate the entire process. A core research problem is identified as part of the first agile process, motivating the researcher and customer toward solutions. An overview of the issue and the importance of finding solutions are provided. As part of the second agile process, solutions are evaluated qualitatively, quantitatively, or using a combination of methods. An artifact's core behavior and structure are deduced by analyzing the created solutions during the third agile process. The fourth, the agile methodology, shows how well you can create artifacts that solve problems through design and development. We planned to perform extensive experiments, simulations, and proofs-of-concept to understand how the artifacts address the core issues. As part of the fifth agile process, the success criteria are compared with the findings or results.  
We are measuring and observing how artifacts support solutions to problems. The proposed solutions' objectives are well matched with the experimental findings through demonstration processes. As a result of this process, researchers can improve artifacts and communicate results for further development. At the end of the agile process, findings will be communicated in relation to the published objectives for peer review. Our proposed future research investigates sniffing attacks on IoMT under the medical implantable communication system (MICS) frequency band ranging from 402 to 406 MHZ using the design science method.  
We planned to use radio frequency machine learning (RFML) utilizing radio frequency machine learning [49], physical emanation security [50], and the internet of medical things. We will develop an open-source testbed for collecting signal intelligence data. We develop a proposed framework for countering or mitigating RF spectrum-based sniffing attacks on IoMT in the healthcare ecosystem. The results and analysis will be evaluated in the testbed. Research issues in spectrum-level physical attacks on IoMT devices will be discussed, including future directions and commercialization.  
Conceptualization, I.A.J. and B.S.; methodology, I.A.J. and B.S.; software, B.S. and S.A.; validation, B.S., S.A. and G.N.S.; formal analysis, I.A.J.; investigation, B.S. and S.A.; resources, S.A.; data curation, I.A.J.; writing--original draft preparation, I.A.J. and B.S.; writing--review and editing, I.A.J.; visualization, I.A.J. and B.S.; supervision, B.S. and S.A.; project administration, S.A. and G.N.S. All authors have read and agreed to the published version of the manuscript.  
The research received no external funding.  
Not applicable.  
The authors would acknowledge the support of the Internet of Things Lab and Energy Resources Institute, Charles Darwin University.  
The authors declare no conflict of interest.