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NTIS 바로가기Journal of Internet Computing and Services = 인터넷정보학회논문지, v.22 no.6, 2021년, pp.83 - 89
권혁진 (Defense Protection and Safety Engineering Department, Seoul National University of Science & Technology) , 김성태 (Management Information Systems at School of Business, Seoul National University, Center for Military Analysis and Planning, Korea Institute for Defense Analyses) , 주예나 (Graduate School Of Information, Yonsei University)
The RMF (Cyber Security Risk Management Framework) is a more strengthened U.S. defense cybersecurity framework that is currently used throughout the U.S. federal government beyond the defense sector. In the past decade, the proportion of cyber warfare in non-regular warfare encountered by the United...
Ho-Yeon Ryu, Young-Ho Nam, "An Attack Model Based on Software Cruise for Information Warfare", Journal of Internet Computing and Services, Vol. 5, No. 5, pp 49-59, 2004. http://www.jics.or.kr/digital-library/260
Seungbae Lee, "Implementation Considerations for Program Protection and Cybersecurity in Weapon Acquisition Systems from U.S.", Vol. 1, No. 2, pp 23-36, 2019.
DoD, "NetOps Strategic Vision", 2018.
Korea University Security Analysis and Evaluation Laboratory, "Research on how to apply the RMF process of the defense acquisition system for cybersecurity test evaluation," Joint Chiefs of Staff's Test and Evaluation Department Service, 2017.
Stephen Cook, Shaun Wilson, "The case for investment in Systems Engineering in the early stages of Projects and Programs", SETE conference, 2018. https://www.shoalgroup.com/wp-content/uploads/2018/05/Cook-Wilson-2018-Case-for-early-stage-investment-inSE-SETE-2018.pdf
DoD, DoD Program Manager's Guiedbook for Integrating the Cybersecurity Risk Management Framework into the System Acquisition Lifecycle, September 2015.
Hu-Chen Liu, FMEA Using Uncertainty Theories and MCDM Methods, Springer, 2016. https://link.springer.com/book/10.1007/978-981-10-1466-6
Craig C. Sherbrooke, "Vari-metric: Improved Approximations for Multi-indenture, Multi-echelon Availability Models", Operations Research, Vol.34, No.2, 1986. https://doi.org/10.1287/opre.34.2.311
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