Cyber-security threats and response models in power plants/ Carol Smidts, Indrajit Ray, Quanyan Zhu, Pavan Kumar Vaddi, Yunfei Zhao, Linan Huang, Xiaoxu Diao, Rakibul Talukdar, Michael C. Pietrykowski.
2022
QA76.9.A25
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Title
Cyber-security threats and response models in power plants/ Carol Smidts, Indrajit Ray, Quanyan Zhu, Pavan Kumar Vaddi, Yunfei Zhao, Linan Huang, Xiaoxu Diao, Rakibul Talukdar, Michael C. Pietrykowski.
Author
ISBN
9783031127113 (electronic bk.)
3031127110 (electronic bk.)
3031127102
9783031127106
3031127110 (electronic bk.)
3031127102
9783031127106
Publication Details
Cham, Switzerland : Springer, 2022.
Language
English
Description
1 online resource
Item Number
10.1007/978-3-031-12711-3 doi
Call Number
QA76.9.A25
Dewey Decimal Classification
005.8
Summary
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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Includes bibliographical references and index.
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Source of Description
Online resource; title from PDF title page (SpringerLink, viewed October 20, 2022).
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Series
SpringerBriefs in computer science, 2191-5776
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Print version: 9783031127106
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Table of Contents
Introduction
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.
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.