사물인터넷융복합논문지 (Journal of Internet of Things and Convergence)

한국사물인터넷학회 (The Korea Internet of Things Society)
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데이터 마이닝 전략을 사용하여 원자력 시스템의 동적 보안을 위한 사물 인터넷 (IoT) 기반 모델링

Internet of Things (IoT) Based Modeling for Dynamic Security in Nuclear Systems with Data Mining Strategy

  • 장경배 (고려사이버대학교 기계제어공학과) ;
  • 백창현 (고려사이버대학교 기계제어공학과) ;
  • 김종민 (고려대학교 전기전자공학부 대학원) ;
  • 백형호 (중원대학교 생체의공학과 대학원) ;
  • 우태호 (고려사이버대학교 기계제어공학과)
  • Jang, Kyung Bae (Dept. of Mechanical and Control Engineering, The Cyber University of Korea) ;
  • Baek, Chang Hyun (Dept. of Mechanical and Control Engineering, The Cyber University of Korea) ;
  • Kim, Jong Min (School of Electrical Engineering, Korea University) ;
  • Baek, Hyung Ho (Dept. of Biomedical Engineering, Jungwon University) ;
  • Woo, Tae Ho (Dept. of Mechanical and Control Engineering, The Cyber University of Korea)
  • 투고 : 2020.11.28
  • 심사 : 2021.01.18
  • 발행 : 2021.03.31
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초록

원자력 테러 예방을 위해 기존의 물리 보호 시스템(PPS)를 수정한 빅데이터 기반의 클라우드 컴퓨팅 시스템과 통합된 데이터 마이닝 디자인이 조사됩니다. 원자력 범죄사건에 대해 시뮬레이션 연구에 의해 테러 관련 기관의 네트워킹이 모델링됩니다. 불법 도청 없이 무고한 사람들을 공격하려는 시도와 테러리즘을 정부가 탐지할 필요가 있습니다. 이 연구의 수학적 알고리즘은 테러 사건의 정확한 결과를 제공할 수 없지만, 시뮬레이션을 통해 잠재적 가능성을 얻을 수 있습니다. 본 결과는 시간에 따른 모양 진동을 보여줍니다. 또한 각 값의 빈도를 통합하면 결과의 전환 정도를 알 수 있습니다. 값은 63.125 시간에 -2.61741로 증가합니다. 따라서 테러 가능성은 나중에 가장 높습니다.

The data mining design incorporated with big data based cloud computing system is investigated for the nuclear terrorism prevention where the conventional physical protection system (PPS) is modified. The networking of terror related bodies is modeled by simulation study for nuclear forensic incidents. It is needed for the government to detect the terrorism and any attempts to attack to innocent people without illegal tapping. Although the mathematical algorithm of the study can't give the exact result of the terror incident, the potential possibility could be obtained by the simulations. The result shows the shape oscillation by time. In addition, the integration of the frequency of each value can show the degree of the transitions of the results. The value increases to -2.61741 in 63.125th hour. So, the terror possibility is highest in later time.

키워드

참고문헌

  1. Daily mail, Widow of poisoned Russian spy Alexander Litvinenko in tearful plea for cash to fund public inquiry into his death, The Mail on Sunday & Metro Media Group, 2013.
  2. IAEA, Guidance for the Application of an Assessment Methodology for Innovative Nuclear Energy Systems INPRO Manual-Physical Protection. IAEA-TECDOC-1575 Rev. 1. IAEA, VIENNA, Austria, 2008.
  3. T.H. Woo, Big data-based data mining modeling for nuclear security analysis in the modified physical protection system. Transactions of the Korean Nuclear Society Autumn Meeting, Pyeongchang, Korea, October 30-31, 2014.
  4. U.S. Department of homeland security, Data Mining Report to Congress. Privacy Office, U.S. Department of Homeland Security, Washington, D.C., 2012, 2013.
  5. P. Russom, Big Data Analytics. TDWI research, fourth quarter 6, 2011.
  6. CIO central guest, Size Doesn't Matter Anymore With Big Data. Forbes, CIONetwork. TECH., 2013.
  7. C.A. Steed, D.M. Ricciuto, G. Shipman, B. Smith, P.E. Thornton, D. Wang, X. Shi, and D.N. Williams, "Big data visual analytics for exploratory earth system simulation analysis" Computers & Geosciences, Vol.61, pp.71-82, 2013. https://doi.org/10.1016/j.cageo.2013.07.025
  8. S. Fiore, A.D. Anca, C. Palazzo, I. Foster, D.N. Williams and G. Aloisio, "Ophidia: Toward Big Data Analytics for eScience" Procedia Computer Science. Vol.18, pp.2376-2385, 2013. https://doi.org/10.1016/j.procs.2013.05.409
  9. I. Ivanov, M. Van Sinderen and B. Shishkov, Cloud Computing and Services Science. Springer, New York, NY, USA, 2012.
  10. J.J.M. Seddon and W.L. Currie, "Cloud computing and trans-border health data: Unpacking U.S. and EU healthcare regulation and compliance," Health Policy and Technology, Vol.2, No.4, pp.229-241, 2012. https://doi.org/10.1016/j.hlpt.2013.09.003
  11. G. Sakellari and G. Loukas, "A survey of mathematical models, simulation approaches and test beds used for research in cloud computing," Simulation Modelling Practice and Theory, Vol. 39, pp.92-103, 2013. https://doi.org/10.1016/j.simpat.2013.04.002
  12. M. Caudill, Neural networks primer, part I. Adaptics Inc., San Diego, CA, USA, 1987.
  13. W.S. McCulloch and W.H. Pitts, "A Logical Calculus of the Ideas Immanent in Nervous Activity," The bulletin of mathematical biophysics. No.7, pp.115-133, 1943.
  14. B. Farley and W.A. Clark, "Simulation of Self-Organizing Systems by Digital Computer," Transactions of the IRE Professional Group on Information Theory. Vol.4, No.4, pp.76-84, 1954. https://doi.org/10.1109/TIT.1954.1057468
  15. Y. Li, J. Peng, B. Liu, W. Li, D. Huang and L. Zhang, "Prediction model of ammonium uranyl carbonate calcination by microwave heating using incremental improved Back-Propagation neural network," Nuclear Engineering and Design. Vol.241, No.5, pp.1909-1913, 2011. https://doi.org/10.1016/j.nucengdes.2010.12.017
  16. T. Bayram, S. Akkoyun and S.O. Kara, "A study on ground-state energies of nuclei by using neural networks," Annals of Nuclear Energy. Vol.63, pp.172-175, 2014. https://doi.org/10.1016/j.anucene.2013.07.039
  17. System dynamics society, The Field of System Dynamics. Albany, NY, USA, 2018.
  18. Kirkwood, System Dynamics Resource Page. Department of Supply Chain Management, Arizona State University, Tempe, AZ, USA, 2013.
  19. K. Pierson and J.D. Sterman, "Cyclical dynamics of airline industry earnings," System Dynamics Review. Vol.29, No.3, pp.129-156, 2013. https://doi.org/10.1002/sdr.1501
  20. J.B. Morrison, J.W. Rudolph and J.S. Carroll, "Dynamic modeling as a multidiscipline collaborative journey," System Dynamics Review. No.29, No.1, pp.4-25, 2013. https://doi.org/10.1002/sdr.1492
  21. B. Palace, Data Mining. Technology Note prepared for Management 274A Anderson Graduate School of Management at UCLA, Los Angeles, CA, USA, 1996.
  22. Y.A. Alsultanny, "Labor Market Forecasting by Using Data Mining," Procedia Computer Science. Vol.18, pp.1700-1709, 2013. https://doi.org/10.1016/j.procs.2013.05.338
  23. A. Pena-Ayala, "Educational data mining: A survey and a data mining-based analysis of recent works," Expert Systems with Applications. Vol.41, No.4, pp.1432-1462, 2014. https://doi.org/10.1016/j.eswa.2013.08.042
  24. C.D. Ferguson, W.C. Potter, A. Sands, L.S. Spector and F.L. Wehling, The Four Faces of Nuclear Terrorism. Center for nonproliferation studies. Monterey Institute of International Studies, Monterey, CA, USA, 2004.
  25. Institute for Economics and Peace (IEP), Global Terrorism Index (GTI), Capturing the Impact of Terrorism from 2002 - 2011, Sydney, Australia, 2012, .
  26. B.K. Lee, "A Study on Workers' Risk-Aware Smart Bands System in Explosive Areas," Journal of The Korea Internet of Things Society, Vol.5, No.2, pp.73-79, 2019. https://doi.org/10.20465/KIOTS.2019.5.2.073
  27. Y.J. Lee, "Analytical Modelling and Heuristic Algorithm for Object Transfer Latency in the Internet of Things," Journal of The Korea Internet of Things Society, Vol.6, No.3, pp.1-6, 2020. https://doi.org/10.20465/KIOTS.2020.6.3.001
  28. D. W. Kim, "Legged Robot Trajectory Generation using Evolved Fuzzy Machine for IoT Environments," Journal of The Korea Internet of Things Society, Vol.6, No.3, pp.59-65, 2020. https://doi.org/10.20465/KIOTS.2020.6.3.059