This book comprises a set of chapters that introduce various topics pertinent to novel approaches towards enhancing cyber-physical measures for increased security and resilience levels in control systems. The unifying theme of these approaches lies in the utilization of knowledge and models of the physical systems, rather than an attempt to reinvigorate conventional IT-based security measures.
The contributing authors present perspectives on network security, game theory, and control, as well as views on how these disciplines can be combined to design resilient, safe, and secure control systems. The book explores how attacks in different forms, such as false data injections and denial-of-service can be very harmful, and may not be detected unless the security measures exploit the physical models. Several applications are discussed, power systems being considered most thoroughly.
Because of its interdisciplinary nature―techniques from systems control, game theory, signal processing and computer science all make contributions―Security and Resilience of Control Systems will be of interest to academics, practitioners and graduate students with a broad spectrum of interests.
Author(s): Hideaki Ishii, Quanyan Zhu
Series: Lecture Notes in Control and Information Sciences, 489
Publisher: Springer
Year: 2022
Language: English
Pages: 236
City: Singapore
Preface
Contents
Part I Resilient Control and Estimation Under Cyber-Attacks
1 Secured Filters Based on Saturated Innovations
1.1 Introduction
1.2 Motivating Examples
1.2.1 Security of Smart Buildings
1.2.2 Security of Autonomous Vehicles
1.3 Problem Formulation
1.3.1 System Model
1.3.2 Attack Model
1.3.3 Problems of Interest
1.4 Secure Centralized Filter Based on Saturated Innovations
1.5 Secure Distributed Filter: A Consensus Method
1.5.1 Graph Preliminaries
1.5.2 Distributed Filter Design
1.5.3 Performance Analysis
1.6 Numerical Simulations
1.7 Conclusion and Future Work
References
2 Zero-Dynamics Attack, Variations, and Countermeasures
2.1 Introduction
2.2 Threats of Zero-Dynamics Attack
2.2.1 Zero-Dynamics Attack
2.2.2 Sampling-Zero-Dynamics Attack
2.2.3 Enforced-Zero-Dynamics Attack
2.2.4 Robust Zero-Dynamics Attack
2.2.5 Zero-Dynamics Attack for Nonlinear Systems
2.3 Disarming Zero-Dynamics Attack
2.3.1 Moving Zeros by Generalized Hold
2.3.2 Optimal Design of Generalized Hold
2.3.3 Moving Zeros by Generalized Sampler
2.3.4 Optimal Design of Generalized Sampler
2.4 Conclusion
References
3 Secure Networked Control Under Jamming Attacks: An SINR-Based Approach
3.1 Introduction
3.2 Networked Control Under State-Dependent Jamming
3.2.1 Transmission Failure Probabilities and Their Relation to Signal-to-Interference-plus-Noise Ratio
3.2.2 Attacker's Capabilities and Constraints in State-Dependent Jamming
3.2.3 A Comparison of the Setups for State-Dependent and Time-Dependent Jamming
3.3 Rolling-Horizon Jamming Attacks: A State-Dependent Optimization-Based Jamming Strategy
3.4 Analysis of Networked Stabilization Under State-Dependent Jamming Attacks
3.5 Numerical Example
3.6 Conclusion
References
Part II Secure Communication and Privacy in Control
4 Resilient Hierarchical Networked Control Systems: Secure Controls for Critical Locations and at Edge
4.1 Introduction
4.2 Resilient Control for Critical Locations
4.2.1 Launching Stealthy Attack
4.2.2 Detecting Stealthy Attack
4.3 Resilient and Safe Control at the Edge
4.3.1 Cooperative Control and Intelligent Adversary
4.3.2 Resilient and Safe Cooperative Control
4.3.3 An Illustrative Example
4.4 Conclusions
References
5 A Tutorial on Security and Privacy Challenges in CPS
5.1 Introduction
5.1.1 Attacks and Security in CPSs
5.1.2 Faults, Attacks, and Privacy
5.1.3 Outline of This Chapter
5.2 Attack Models
5.2.1 Disclosure Attacks
5.2.2 Deception Attacks
5.2.3 Disruption Attacks
5.3 Common Techniques Against Deception and Disruption
5.3.1 Resilience Mechanisms
5.3.2 Detection Mechanisms
5.4 Summary and Future Directions
5.4.1 CPS-Security of AI-Driven CPSs
5.4.2 AI for Cyber-Security
5.4.3 Scalability
5.4.4 Toward More Realistic Cyber-Security Solutions
References
Part III Cyber-Physical Security for Applications
6 A Low-Cost Approach to Securing Commercial GPS Receivers Against Spoofing Attacks
6.1 Introduction
6.2 Literature Review and Contributions
6.3 Background
6.3.1 GPS Operation Principle
6.3.2 GPS Receivers
6.4 Attack Model
6.4.1 Code Level Attacks
6.4.2 Navigation Message Attacks
6.4.3 Experimental Confirmation of Spoofing-Attack Models
6.5 Security Approach
6.5.1 Ephemeris Validation
6.5.2 Doppler Frequency Validation (Static Receiver Case)
6.5.3 Doppler Frequency Validation (Mobile Receiver)
6.6 Results and Analysis
6.6.1 Spoofing Detection Rate Analysis
6.6.2 False Positives and Threshold Selection
6.6.3 Limitation of the Approach
6.7 Conclusions
References
7 A System-of-Systems Approach to Strategic Cyber-Defense and Robust Switching Control Design for Cyber-Physical Wind Energy Systems
7.1 Introduction
7.1.1 Related Work
7.1.2 Notation
7.1.3 Organization of the Chapter
7.2 System-of-Systems Framework
7.3 WES Modeling and Cyberattack Models
7.3.1 Modeling of WES
7.3.2 WES System Representation
7.3.3 Adversarial Attacks Modeling
7.4 Robust and Resilient Cyber-Aware Switching Control Design
7.4.1 MJLS Model of WES
7.4.2 Cyber-Aware Robust Switching Controller Design
7.4.3 WES Resilience
7.5 Noncooperative Game-Theoretic Control-Aware Cyber-System Design
7.5.1 Control-Aware Cyber-Defense Game
7.5.2 Control-Aware Nash Equilibrium
7.6 Interdependent WES Analysis and Design
7.6.1 System-of-Systems Equilibrium
7.6.2 Iterative Algorithm
7.7 Case Studies
7.7.1 Cyber-Aware Robust Switching Control
7.7.2 Impact of Security and Resilience
7.7.3 Integrated Cyber-Physical WES Design
7.8 Conclusion
References
8 Machine Learning-Based and Physics-Based Attack Resilient Wide-Area Monitoring, Protection and Control Systems
8.1 Introduction
8.2 Attack Surface Analysis for CPS Control Loop
8.2.1 Overview of the CPS Architecture
8.2.2 CPS Security Challenges and Requirements
8.3 Attack-Resilient SCADA and WAMPAC
8.3.1 Proposed Attack-Resilient Framework for SCADA and WAMPAC
8.3.2 Control Center Network Modeling
8.3.3 Cyber-Physical Control Model
8.3.4 A Multi-layer Intrusion and Anomaly Detection System
8.3.5 Physics Model-Based Mitigation for WAMPAC Applications
8.3.6 Deep Learning and Machine Learning for Anomaly Detection
8.3.7 CPS Grid Resiliency and Restoration
8.4 HIL CPS Security Smart Grid Testbed
8.5 Case Study: Attack-Resilient WADC Using Machine Learning
8.5.1 Machine Learning-Based Anomaly Detection for WADC
8.5.2 Results and Discussion
8.6 Conclusion
References
Index
491256_1_En_BookBackmatter_OnlinePDF.pdf
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