Abstract
Among the many hacking attempts carried out against information systems for the past few years, cyber-attacks that could lead to a national-level threat included attacks against nuclear facilities particularly nuclear power stations. Two of the typical examples are the Stuxnet attack against an Iranian nuclear facility and the cyber threat against Korea Hydro and Nuclear Power in December 2015. The former has proven that a direct cyber-attack can actually stop the nuclear power station, and the latter has shown that people can be terrorized with only a (cyber) threat. After these incidents, security measures for cyber-attacks against industrial control systems have been strengthened. The nuclear power stations also changed their passive concept of executing security measures by operating the plant with an isolated network to prepare for the cyber-attacks carried out by malicious codes. The difference between the two concepts is that the latter has been formulated based on the possibility that most of the control systems can be targets of cyber-attacks. Threats against control systems are gradually increasing nowadays, so the relevant industries are implementing some measures to identify/develop safe and reliable digital equipment and identify risks to establish effective cyber security plans. Thus, this paper proposes a security measure based on the classification of past attack incidents against control systems and the big data analysis technique that processes the data generated from individual security equipment. The security of control systems is expected to be strengthened through such effective measure.



















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Lee S, Huh JH (2017) An efficient nuclear power plant security measure using big data analysis approach. In: The 2017 international conference on future information technology, applications and services, IFIT 2017, p 1
Huh JH, Kim TJ (2018) A location-based mobile health care facility search system for senior citizens. J Supercomput. https://doi.org/10.1007/s11227-018-2342-5
Tankard C (2012) Big data security. Netw Secur 7:5–8
Kim GH, Trimi S, Chung JH (2014) Big-data applications in the government sector. Commun ACM 57(3):78–85
Eom S, Huh JH (2018) Group signature with restrictive linkability: minimizing privacy exposure in ubiquitous environment. J Ambient Intell Human Comput. https://doi.org/10.1007/s12652-018-0698-2
Hirose K (2012) 2011 Fukushima Dai-ichi nuclear power plant accident: summary of regional radioactive deposition monitoring results. J Environ Radioactivity 111:13–17
Jakóbik A (2016) Big data security. In: Pop F, Kołodziej J, Di Martino B (eds) Resource management for big data platforms. Springer, Cham, pp 241–261
NIST Special Publication 1500-4 NIST big data interoperability. In: Security and privacy. NIST Big Data Public Working Group
He D, Jiajun B, Chan S (2013) Handauth: efficient handover authentication with conditional privacy for wireless networks. IEEE Trans Comput IEEE 62(3):616–622
Schneier B (2007) Applied cryptography protocols, algorithms, and source code in C. Wiley, New York, pp 1–34
Stallings W (2003) Cryptography and network security: principles and practice. Pearson, London, pp 1–16
Kitchin R (2014) The real-time city? Big data and smart urbanism. GeoJournal 79(1):1–14
Sola J, Sevilla J (1997) Importance of input data normalization for the application of neural networks to complex industrial problems. IEEE Trans Nuclear Sci 44(3):1464–1468
Pazhanirajaa N, Victer Paula P, Saleem Bashab MS, Dhavachelvanc P (2015) Big data and hadoop—a study in security perspective. In: Procedia computer science, 2nd International Symposium on Big Data and Cloud Computing (ISBCC’15), vol 50. Elsevier, pp 596–601
Birkenmeier GF, Park JK, Rizvi ST (2008) Ring hulls of semi prime homomorphic images. In: Brzeziński T, Gómez Pardo JL, Shestakov I, Smith PF (eds) Modules and comodules. Springer, New York, pp 101–111
Birkenmeier GF, Park JK, Rizvi ST (2010) Principally quasi-Baer ring hulls. In: Van Huynh D, López-Permouth SR (eds) Advances in ring theory. Springer, Verlag Basel/Switzerland, pp 47–61
Lantz B (2013) Machine learning with R. Packt Publishing Ltd., Birmingham
Hao F, Park DS, Woo SY, Min SD, Park S (2016) Treatment planning in smart medical: a sustainable strategy. J Inf Process Syst 12(4):711–723
Silver David et al (2016) Mastering the game of Go with deep neural networks and tree search. Nature 529:484–489
Joo JW, Lee JK, Park JH (2015) Security considerations for a connected car. J Converg 6:1–9
Sharma PK, Moon SY, Park JH (2017) Block-VN: a distributed blockchain based vehicular network architecture in smart city. J Inf Process Syst 13:184–195
González-Aparicio MT, Ogunyadeka A, Younas M, Tuya J, Casado R (2017) Transaction processing in consistency-aware user’s applications deployed on NoSQL databases. Hum Centric Comput Inf Sci 7(7):1–12
Ngu HCV, Huh J-H (2016) B + -tree construction on massive data with Hadoop. In: Hariri S (ed) Cluster computing. Springer, New York, pp 1–11
Lu T, Guo X, Xu B, Zhao L, Peng Y, Yang H (2013) Next big thing in big data: the security of the ICT supply chain. In: International Conference on Social Computing (SocialCom). IEEE, pp 1066–1073
Cardenas AA, Manadhata PK, Rajan SP (2013) Big data analytics for security. IEEE Secur Priv 11(6):74–76
Huh Jun-Ho, Seo Kyungryong (2016) Design and test bed experiments of server operation system using virtualization technology. Hum Centric Comput Inf Sci 6(1):1–21
Zhao G, Rong Ch, Gilje Jaatun M, Sandnes FE (2012) Reference deployment models for eliminating user concerns on cloud security. J Supercomput 61(2):337–352
Huh J-H (2017) PLC-based design of monitoring system for ICT-integrated vertical fish farm. Hum Centric Comput Inf Sci 7(20):1–19
Patil HK, Seshadri R (2014) Big data security and privacy issues in healthcare. In: 2014 IEEE International Congress on Big Data (BigData Congress). IEEE, pp 762–765
Huh JH (2018) Implementation of lightweight intrusion detection model for security of smart green house and vertical farm. Int J Distrib Sens Netw 14(4):1–11
Vosoughi S, Roy D, Aral S (2018) The spread of true and false news online. Science 359:1146–1151
Jordan MI, Mitchell TM (2015) Machine learning: trends, perspectives, and prospects. Science 349:255–260
Huh Jun-Ho (2018) Big data analysis for personalized health activities: machine learning processing for automatic keyword extraction approach. Symmetry 10(4):1–30
Moon Seo Yeon, Park Jong Hyuk (2016) Efficient hardware-based code convertor of a quantum computer. J Converg 7:1–9
Liu H, Gegov A, Cocea A (2016) Rule based systems for big data a machine learning approach. Springer, New York, pp 1–43
Medeiros J, Schirru R (2008) Identification of nuclear power plant transients using the Particle Swarm Optimization algorithm. Ann Nucl Energy 35(4):576–582
Huh J-H, Otgonchimeg S, Seo K (2016) Advanced metering infrastructure design and test bed experiment using intelligent agents: focusing on the PLC network base technology for Smart Grid system. J Supercomput 72(5):1862–1877
Feng D, Zhang M, Li H (2014) Big data security and privacy protection. Chin J Comput 37(1):246–258
Huh J-H (2017) Smart grid test bed using OPNET and power line communication. In: Naumann F, Shasha D, Vossen G (eds) Advances in computer and electrical engineering. IGI Global, Pennsylvania, pp 1–425
Hashem IAT, Yaqoob I, Anuar NB, Mokhtar S, Gani A, Khan SU (2015) The rise of “big data” on cloud computing: review and open research issues. Inf Syst 47:98–115
Hewitt C (1991) Open information systems semantics for distributed artificial intelligence. Artif Intell 47(1–3):79–106
Acknowledgements
This work was supported by the National Research Foundation of Korea (NRF) Grant funded by the Korea government (MSIT) (No. 2017R1C1B5077157).
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Lee, S., Huh, JH. An effective security measures for nuclear power plant using big data analysis approach. J Supercomput 75, 4267–4294 (2019). https://doi.org/10.1007/s11227-018-2440-4
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DOI: https://doi.org/10.1007/s11227-018-2440-4