The Internet of Things (IoT) provides data convergence and sharing functions, and IoT technology is the most fundamental core technology in creating new services by convergence of various cutting-edge technologies. However, there are different classification systems for the Internet of Things, and when it is limited to the domestic public sector, it is difficult to properly grasp the current status of which devices are installed and operated with what share, and systematic data or research The results are very difficult to find. Therefore, in this study, the relevance of the classification system for IoT devices was analyzed according to reality based on sales, shipments, and growth rate, and based on this, the actual share of IoT devices among domestic public institutions was analyzed in detail. The derived detailed analysis results are expected to be efficiently utilized in the process of selecting IoT devices for research and analysis to advance information protection technology such as responding to malicious code attacks on IoT devices, analyzing incidents, and strengthening security vulnerabilities.
S.N.Swamy and S.R.Kota, "An Empirical Study on System Level Aspects of Internet of Things (IoT),"IEEE Access, Vol.8,pp.188082-188134, 2020.
E. Kim, K. Kim, C. Leem, C. Lee, “A Study on Development and Application of Taxonomy of Internet of Things Service,” The Journal of Society for e-Business Studies, Vol.20, No.2, May 2015, pp.107-123.
Alfonso, V., Eric, G., Sree, C., and Jouni, F., Market Trends: TSPs Must Invest in the Rapidly Evolving IoT Ecosystems Now, Gartner, 2013.
Ministry of Science and ICT, NIPA, 2020 IoT Industry Survey, 2020.
NIPA, GIP Global ICT Portal, Global IoT(Internet of Things) Market, 2020
Ministry of the Interior and Safety, NIPA, Government guidelines for IoT adoption, 2019.
Gartnet, Internet of Things: Unlocking True Digital Business Potential, https://www.gartner.com/en/information-technology/insights/internet-of-things
IDC, Worldwide Intenet of Things Forecast, 2020-2024. https://www.idc.com/getdoc.jsp?containerId=US45861420
IDC, IDC: Global IoT Market Report, 2021. https://medium.com/tech-in-china/idc-global-iot-ma rket-report-5cb5be303e51
H.Lee, "Intrusion Artifact Acquisition Method based on IoT Botnet Malware," Journal of The Korea Internet of Things Society, Vol.7, No.3, pp.1-8, 2021.
S.Ramesh and M.Govindarasu, "An Efficient Framework for Privacy-Preserving Computations on Encrypted IoT Data," in IEEE Internet of Things Journal, Vol.7, No.9, pp.8700-8708, 2020.
H.Seo, J.K.Park, "The prevent method of data loss due to differences in bit rate between heterogeneous IoT devices," Journal of the Korea Institute of Information and Communication Engineering, Vol.23, No.7, pp.829~836, 2019.
Maria Stoyanova, Yannis Nikoloudakis, Spyridon Panagiotakis, Evangelos Pallis, and Evangelos K. Markakis, “A Survey on the Internet of Things (IoT)Forensics: Challenges, Approaches, and Open Issues,”IEEE COMMUNICATIONS SURVEYS & TUTORIALS, Vol.22, No.2, pp.1191-1221, SECOND QUARTER 2020.
Ibrar Yaqoob, Ibrahim Abaker Targio Hashem, Arif Ahmed, S. M. Ahsan Kazmia, Choong Seon Hong, “Internet of things forensics: Recent advances, taxonomy, requirements, and open challenges,”Future Generation Computer Systems · September 2018.
M. Wazzan, D. Algazzawi, O. Bamasaq, A. Albeshri, L. Cheng, “Internet of Things Botnet Detection Approaches: Analysis and Recommendations for Future Research,” Applied Science Vol.11, 5713, 2021.
A. Alenezi, H. Atlam, R. Alsagri, M. Alassafi, and G. Wills, “IoT Forensics: A State-of-the-Art Review, Challenges and Future Directions,” Proceedings of the 4th International Conference on Complexity, Future Information Systems and Risk (COMPLEXIS 2019), pages 106-115.
Weam Saadi Hamza, Hassan Muayad Ibrahim, Methaq Abdullah Shyaa, Jane J. Stephan, “IoT Botnet Detection: Challenges and Issues,” Test Engineering &Management, Vol.83, pp.15092-15097, 2020.