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This title is printed to order. This book may have been self-published. If so, we cannot guarantee the quality of the content. In the main most books will have gone through the editing process however some may not. We therefore suggest that you be aware of this before ordering this book. If in doubt check either the author or publisher’s details as we are unable to accept any returns unless they are faulty. Please contact us if you have any questions.
This 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.
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This title is printed to order. This book may have been self-published. If so, we cannot guarantee the quality of the content. In the main most books will have gone through the editing process however some may not. We therefore suggest that you be aware of this before ordering this book. If in doubt check either the author or publisher’s details as we are unable to accept any returns unless they are faulty. Please contact us if you have any questions.
This 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.