# Towards Design and Development of Security Assessment Framework for Internet of Medical Things
## 6 Conclusions and Future Work  
Medical devices are unsecure in the design and post-market phases and may be vulnerable to cyber threats as the quantity and complexity of cyber threats grow. Similarly, the healthcare data generated by these devices are also unsecure. If their vulnerabilities are not addressed and remedied, these dangers can be leveraged as an entry point into a hospital. Cyber threats have a huge attack surface, which might disrupt healthcare and possibly put patients' lives in jeopardy. Because healthcare data generated by the devices are sent to the cloud for processing, any modification to the data during processing may threaten the lives of patients. With the growing number of connected medical devices, the probability of being exposed to attack surfaces and vulnerabilities by malevolent attackers is increasing. It is important to counter cyberattacks by including security methods to reduce attacks. This study proposes a security assessment of different medical devices in the design and post-market phases and data security assessment. This research investigates a conceptual model that incorporates increased security principles into the design and implementation of medical instruments as well as data protection during handling. This framework is used for medical devices and healthcare data security assessment and develops the security algorithm for data security. To evaluate the security of devices and data, the authors applied an integrated fuzzy AHP TOPSIS approach in the proposed model. This methodology is useful for the assessment of cyber threats to devices and data and the development of a security algorithm for securing healthcare data.  
The suggested framework can safely and securely enhance medical device interoperability and healthcare data security in healthcare, which is essential to protect patients' healthcare data privacy. The framework has the ability to check different healthcare devices' security, as well as the efficiency of the security mechanisms used in mitigating or blocking attacks. Regardless of the fact that our research study makes use of the potential of integrated fuzzy AHP TOPSIS, numerous methods for identifying and prioritizing security performance measures for IoMT devices could be incorporated with fuzzy logic. As a result, in future work, numerous different MCDM tactics, such as ANP, ELECTRA, VIKOR, PROMETHEUS, and so on, may be employed for comparative evaluation.  
**Author Contributions:** Conceptualization, F.A.A. and M.T.J.A.; Data curation, F.A.A., M.A. and M.T.J.A.; Formal analysis, F.A.A., M.A. and M.T.J.A.; Funding acquisition, F.A.A.; Investigation, F.A.A. and M.T.J.A.; Methodology, F.A.A. and M.T.J.A.; Project administration, F.A.A. and M.T.J.A.; Resources, M.A. and M.T.J.A.; Software, F.A.A., M.A. and M.T.J.A.; Supervision, F.A.A. and M.T.J.A.; Validation, M.A. and M.T.J.A.; Visualization, M.A. and M.T.J.A.; Writing--original draft, F.A.A., M.A. and M.T.J.A.; Writing--review & editing, F.A.A. All authors have read and agreed to the published version of the manuscript.  
**Funding:** The work is funded by grant number 12-INF2970-10 from the National Science, Technology and Innovation Plan (MAARIFAH), the King Abdul-Aziz City for Science and Technology (KACST), Kingdom of Saudi Arabia.  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** Not applicable.  
**Acknowledgments:** We thank the Science and Technology Unit at Umm Al-Qura University for their continued logistics support.  
**Conflicts of Interest:** The authors declare no conflict of interest.