000 | 05329nam a22006495i 4500 | ||
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001 | 978-3-031-12711-3 | ||
003 | DE-He213 | ||
005 | 20240423130142.0 | ||
007 | cr nn 008mamaa | ||
008 | 221010s2022 sz | s |||| 0|eng d | ||
020 |
_a9783031127113 _9978-3-031-12711-3 |
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024 | 7 |
_a10.1007/978-3-031-12711-3 _2doi |
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050 | 4 | _aQA76.9.A25 | |
072 | 7 |
_aUR _2bicssc |
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072 | 7 |
_aUTN _2bicssc |
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_aCOM053000 _2bisacsh |
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072 | 7 |
_aUR _2thema |
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072 | 7 |
_aUTN _2thema |
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082 | 0 | 4 |
_a005.8 _223 |
100 | 1 |
_aSmidts, Carol. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut |
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245 | 1 | 0 |
_aCyber-Security Threats and Response Models in Nuclear Power Plants _h[electronic resource] / _cby Carol Smidts, Indrajit Ray, Quanyan Zhu, Pavan Kumar Vaddi, Yunfei Zhao, Linan Huang, Xiaoxu Diao, Rakibul Talukdar, Michael C. Pietrykowski. |
250 | _a1st ed. 2022. | ||
264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2022. |
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300 |
_aX, 93 p. 30 illus. _bonline resource. |
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336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
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338 |
_aonline resource _bcr _2rdacarrier |
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347 |
_atext file _bPDF _2rda |
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490 | 1 |
_aSpringerBriefs in Computer Science, _x2191-5776 |
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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. | ||
650 | 0 | _aData protection. | |
650 | 0 | _aCooperating objects (Computer systems). | |
650 | 0 | _aNuclear engineering. | |
650 | 1 | 4 | _aData and Information Security. |
650 | 2 | 4 | _aCyber-Physical Systems. |
650 | 2 | 4 | _aNuclear Energy. |
700 | 1 |
_aRay, Indrajit. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut |
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700 | 1 |
_aZhu, Quanyan. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut |
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700 | 1 |
_aVaddi, Pavan Kumar. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut |
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700 | 1 |
_aZhao, Yunfei. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut |
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700 | 1 |
_aHuang, Linan. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut |
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700 | 1 |
_aDiao, Xiaoxu. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut |
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700 | 1 |
_aTalukdar, Rakibul. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut |
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700 | 1 |
_aPietrykowski, Michael C. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut |
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710 | 2 | _aSpringerLink (Online service) | |
773 | 0 | _tSpringer Nature eBook | |
776 | 0 | 8 |
_iPrinted edition: _z9783031127106 |
776 | 0 | 8 |
_iPrinted edition: _z9783031127120 |
830 | 0 |
_aSpringerBriefs in Computer Science, _x2191-5776 |
|
856 | 4 | 0 | _uhttps://doi.org/10.1007/978-3-031-12711-3 |
912 | _aZDB-2-SCS | ||
912 | _aZDB-2-SXCS | ||
942 | _cSPRINGER | ||
999 |
_c185610 _d185610 |