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001			394148
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008			221010s2022 sz | s |||| 0|eng d
020			_a9783031127113
024	7		_a10.1007/978-3-031-12711-3 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC
100	1		_aSmidts, Carol _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut
245	1	0	_aCyber-Security Threats and Response Models in Nuclear Power Plants _cby Carol Smidts, Indrajit Ray, Quanyan Zhu, Pavan Kumar Vaddi, Yunfei Zhao, Linan Huang, Xiaoxu Diao, Rakibul Talukdar, Michael C Pietrykowski
250			_a1st edition 2022
264		1	_aCham _bSpringer International Publishing _c2022
300			_a1 recurso en línea (X, 93 páginas) _b30 illus
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
490	0		_aSpringerBriefs in Computer Science _x2191-5776
505	0		_aIntroduction -- Probabilistic Risk Assessment: Nuclear Power Plants and Introduction to the Context of Cyber Security -- Machine Learning based Abnormal Event Detection and Classification -- Game-Theoretic Design of Response Systems -- Experimental Testbeds and Design of Experiments -- Conclusions.
520			_aThis SpringerBrief presents a brief introduction to probabilistic risk assessment (PRA), followed by a discussion of abnormal event detection techniques in industrial control systems (ICS). It also provides an introduction to the use of game theory for the development of cyber-attack response models and a discussion on the experimental testbeds used for ICS cyber security research. The probabilistic risk assessment framework used by the nuclear industry provides a valid framework to understand the impacts of cyber-attacks in the physical world. An introduction to the PRA techniques such as fault trees, and event trees is provided along with a discussion on different levels of PRA and the application of PRA techniques in the context of cybersecurity. A discussion on machine learning based fault detection and diagnosis (FDD) methods and cyber-attack detection methods for industrial control systems are introduced in this book as well. A dynamic Bayesian networks based method that can be used to detect an abnormal event and classify it as either a component fault induced safety event or a cyber-attack is discussed. An introduction to the stochastic game formulation of the attacker-defender interaction in the context of cyber-attacks on industrial control systems to compute optimal response strategies is presented. Besides supporting cyber-attack response, the analysis based on the game model also supports the behavioral study of the defender and the attacker during a cyber-attack, and the results can then be used to analyze the risk to the system caused by a cyber-attack. A brief review of the current state of experimental testbeds used in ICS cybersecurity research and a comparison of the structures of various testbeds and the attack scenarios supported by those testbeds is included. A description of a testbed for nuclear power applications, followed by a discussion on the design of experiments that can be carried out on the testbed and the associated results is covered as well. This SpringerBrief is a useful resource tool for researchers working in the areas of cyber security for industrial control systems, energy systems and cyber physical systems. Advanced-level students that study these topics will also find this SpringerBrief useful as a study guide.
700	1		_aRay, Indrajit _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut
700	1		_aZhu, Quanyan _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut
700	1		_aVaddi, Pavan Kumar _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut
700	1		_aZhao, Yunfei _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut
700	1		_aHuang, Linan _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut
700	1		_aDiao, Xiaoxu _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut
700	1		_aTalukdar, Rakibul _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut
700	1		_aPietrykowski, Michael C _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut
776	0	8	_iPrinted edition: _z9783031127106
776	0	8	_iPrinted edition: _z9783031127120
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-12711-3 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
988			_aSpringer_Computer_2022
999			_c394148 _d394148