Cyber-Security Threats and Response Models in Nuclear Power Plants

This SpringerBrief provides an introduction to probabilistic risk assessment (PRA) and abnormal event detection techniques in industrial control systems (ICS). It also discusses the use of game theory for developing cyber-attack response models and experimental testbeds used for ICS cybersecurity research. The PRA framework is used to understand the impacts of cyber-attacks in the physical world, and machine learning-based FDD methods and cyber-attack detection methods are introduced. A dynamic Bayesian networks-based method is discussed for detecting abnormal events and classifying them as component faults or cyber-attacks. The stochastic game formulation of the attacker-defender interaction is presented to compute optimal response strategies. Experimental testbeds are used to support cyber-attack response and behavioral study of defenders and attackers during a cyber-attack.

Format: Paperback / softback
Length: 93 pages
Publication date: 11 October 2022
Publisher: Springer International Publishing AG

This SpringerBrief provides a comprehensive introduction to probabilistic risk assessment (PRA), followed by a detailed discussion of abnormal event detection techniques in industrial control systems (ICS). It also offers an insightful introduction to the use of game theory for developing cyber-attack response models and highlights the experimental testbeds employed in ICS cyber security research.

The probabilistic risk assessment framework employed by the nuclear industry serves as a valuable framework for understanding the consequences of cyber-attacks in the physical realm. This brief introduces PRA techniques such as fault trees and event trees, delves into different levels of PRA, and explores their application in the realm of cybersecurity. Furthermore, this book explores machine learning-based fault detection and diagnosis (FDD) methods and cyber-attack detection methods for industrial control systems.

A novel approach is presented, involving a dynamic Bayesian network-based method capable of detecting abnormal events and categorizing them as either component fault-induced safety events or cyber-attacks. Additionally, the stochastic game formulation of the attacker-defender interaction in the context of cyber-attacks on industrial control systems is discussed, enabling the computation of optimal response strategies.

Beyond supporting cyber-attack response, the game model analysis provides valuable insights into the behavioral study of both the defender and the attacker during a cyber-attack. These findings can then be utilized to assess the risk posed to the system by a cyber-attack.

A brief review of the current state of experimental testbeds used in ICS cybersecurity research is presented, along with a comparison of the structures and attack scenarios supported by various testbeds. This comprehensive exploration of PRA, abnormal event detection techniques, game theory, and experimental testbeds in ICS cyber security provides valuable insights for professionals and researchers in the field.

Weight: 174g
Dimension: 235 x 155 (mm)
ISBN-13: 9783031127106
Edition number: 1st ed. 2022