International Journal of Education and Management Engineering (IJEME)
IJEME Vol. 14, No. 2, 8 Apr. 2024
Cover page and Table of Contents: PDF (size: 928KB)
Determination of Security Factors Affecting Internet of Medical Things by Artificial Intelligence Technique
PDF (928KB), PP.41-52
Views: 0 Downloads: 0
Author(s)
Mohd Nadeem
1,*
Prabhash Chandra Pathak
1
Mahfooz Ahmad
2
Masood Ahmad
3
Index Terms
IoMT, IoT, Fuzzy AHP, AI, Healthcare Security, Fuzzy TOPSIS
Abstract
In the age of computing, there is a vast assortment of medical equipment and software available. Software and medical equipment that can be online connected to healthcare Information Technology (IT) systems are referred to as Internet of Medical Things (IoMT). This research study elaborates healthcare connectivity and its security issues to the different dimension of IoMT. During the pandemic situation in 2020-21 Covid, importance of virtualization and its dependencies have got the momentum. The security challenge of IoMT needs to be addressed. The research analysis is evaluating the impact of security factors in IoMT. By systematically evaluating research studies based on the keywords IoMT, security of IoMT, and security in healthcare sector, security attributes and factors were discovered from the different digital library. This evaluation uses soft computing and Artificial Intelligence (AI) techniques, quantitatively elaborates the factors of IoMT and their impact based on security. The results provide guidance for the development of IoMT with security attributes that can help to ensure the security of the device and software based applications on networks or in the cloud. To assess the importance of the criteria and the ranking of the alternatives, the AI technique of Analytic Hierarchy Process (AHP) and Technique for Order of Preferences by Similarity to Ideal Solution (TOPSIS) were applied. The hybrid Fuzzy AHP, Fuzzy TOPSIS techniques are utilizing the concept of decision making in security of IoMT. The items were evaluated using a multi rules choice investigation with several standards. In this research study, eight factors and ten alternatives of IoMT were selected to determine their impact on security. The creating new funding, operating and business model factor of IoMT got the top weight and successfully navigating regulatory change got the least. The AI research on IoMT security determination helps the developer, medical practitioner, and medical device operator to consider the impact of security in IoMT.
Cite This Paper
Mohd. Nadeem, Prabhash Chandra Pathak, Mahfooz Ahmad, Masood Ahmad, "Determination of Security Factors Affecting Internet of Medical Things by Artificial Intelligence Technique", International Journal of Education and Management Engineering (IJEME), Vol.14, No.2, pp. 41-52, 2024. DOI:10.5815/ijeme.2024.02.04
Reference
[1]N. Homer et al., “HIPAA, the Privacy Rule, and Its Application to Health Research,” PLoS Genet., vol. 4, no. 8, Aug. 2009, doi: 10.1371/JOURNAL.PGEN.1000167.
[2]L. P. Verma and M. Kumar, “An IoT based Congestion Control Algorithm,” Internet of Things, vol. 9, p. 100157, Mar. 2020, doi: 10.1016/J.IOT.2019.100157.
[3]U. K. Lilhore et al., “Design and Implementation of an ML and IoT Based Adaptive Traffic-Management System for Smart Cities,” Sensors 2022, Vol. 22, Page 2908, vol. 22, no. 8, p. 2908, Apr. 2022, doi: 10.3390/S22082908.
[4]A. Khraisat, I. Gondal, P. Vamplew, and J. Kamruzzaman, “Survey of intrusion detection systems: techniques, datasets and challenges,” Cybersecurity, vol. 2, no. 1, pp. 1–22, Dec. 2019, doi: 10.1186/S42400-019-0038-7/FIGURES/8.
[5]G. Thamilarasu, A. Odesile, and A. Hoang, “An intrusion detection system for internet of medical things,” IEEE Access, vol. 8, pp. 181560–181576, 2020, doi: 10.1109/ACCESS.2020.3026260.
[6]J. Almalki et al., “Enabling Blockchain with IoMT Devices for Healthcare,” Inf. 2022, Vol. 13, Page 448, vol. 13, no. 10, p. 448, Sep. 2022, doi: 10.3390/INFO13100448.
[7]L. Syed, S. Jabeen, M. S., and A. Alsaeedi, “Smart healthcare framework for ambient assisted living using IoMT and big data analytics techniques,” Futur. Gener. Comput. Syst., vol. 101, pp. 136–151, Dec. 2019, doi: 10.1016/J.FUTURE.2019.06.004.
[8]R. Pratap Singh, M. Javaid, A. Haleem, R. Vaishya, and S. Ali, “Internet of Medical Things (IoMT) for orthopaedic in COVID-19 pandemic: Roles, challenges, and applications,” J. Clin. Orthop. Trauma, vol. 11, no. 4, pp. 713–717, Jul. 2020, doi: 10.1016/J.JCOT.2020.05.011.
[9]S. R. Khan, M. Sikandar, A. Almogren, I. Ud Din, A. Guerrieri, and G. Fortino, “IoMT-based computational approach for detecting brain tumor,” Futur. Gener. Comput. Syst., vol. 109, pp. 360–367, Aug. 2020, doi: 10.1016/J.FUTURE.2020.03.054.
[10]P. Savadjiev et al., “Demystification of AI-driven medical image interpretation: past, present and future,” Eur. Radiol., vol. 29, no. 3, pp. 1616–1624, Mar. 2019, doi: 10.1007/S00330-018-5674-X/TABLES/2.
[11]A. K. Rangarajan and H. K. Ramachandran, “A preliminary analysis of AI based smartphone application for diagnosis of COVID-19 using chest X-ray images,” Expert Syst. Appl., vol. 183, p. 115401, Nov. 2021, doi: 10.1016/J.ESWA.2021.115401.
[12]A. Ferrag, I. A. Jayaraj, B. Shanmugam, S. Azam, and G. N. Samy, “A Systematic Review of Radio Frequency Threats in IoMT,” J. Sens. Actuator Networks 2022, Vol. 11, Page 62, vol. 11, no. 4, p. 62, Sep. 2022, doi: 10.3390/JSAN11040062.
[13]“Top 5 Factors Affecting the Performance of IoMT Devices.” https://www.citiustech.com/blog/top-5-factors-affecting-the-performance-of-iomt-devices (accessed Dec. 13, 2022).
[14]C. H. Yang, Y. Y. Liu, C. H. Chiang, and Y. W. Su, “National IoMT platform strategy portfolio decision model under the COVID-19 environment: based on the financial and non-financial value view,” Ann. Oper. Res., p. 1, 2022, doi: 10.1007/S10479-022-05016-4.
[15]R. Dwivedi, D. Mehrotra, and S. Chandra, “Potential of Internet of Medical Things (IoMT) applications in building a smart healthcare system: A systematic review,” J. Oral Biol. Craniofacial Res., vol. 12, no. 2, p. 302, Mar. 2022, doi: 10.1016/J.JOBCR.2021.11.010.
[16]I. V. Pustokhina, D. A. Pustokhin, D. Gupta, A. Khanna, K. Shankar, and G. N. Nguyen, “An Effective Training Scheme for Deep Neural Network in Edge Computing Enabled Internet of Medical Things (IoMT) Systems,” IEEE Access, vol. 8, pp. 107112–107123, 2020, doi: 10.1109/ACCESS.2020.3000322.
[17]M. Ahmad et al., “Healthcare device security assessment through computational methodology,” Comput. Syst. Sci. Eng., vol. 41, no. 2, 2022, doi: 10.32604/csse.2022.020097.
[18]R. W. Saaty, “The analytic hierarchy process—what it is and how it is used,” Math. Model., vol. 9, no. 3–5, pp. 161–176, Jan. 1987, doi: 10.1016/0270-0255(87)90473-8.
[19]F. A. Alzahrani, M. Ahmad, M. Nadeem, R. Kumar, and R. A. Khan, “Integrity Assessment of Medical Devices for Improving Hospital Services,” Comput. Mater. Contin., vol. 67, no. 3, p. 3619, Mar. 2021, doi: 10.32604/CMC.2021.014869.
[20]H. Alyami et al., “The evaluation of software security through quantum computing techniques: A durability perspective,” Appl. Sci., vol. 11, no. 24, 2021, doi: 10.3390/app112411784.
[21]T. L. Saaty, “A scaling method for priorities in hierarchical structures,” J. Math. Psychol., vol. 15, no. 3, pp. 234–281, Jun. 1977, doi: 10.1016/0022-2496(77)90033-5.
[22]M. Alenezi, A. Agrawal, R. Kumar, and R. A. Khan, “Evaluating Performance of Web Application Security through a Fuzzy Based Hybrid Multi-Criteria Decision-Making Approach: Design Tactics Perspective,” IEEE Access, vol. 8, pp. 25543–25556, 2020, doi: 10.1109/ACCESS.2020.2970784.