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Cross-Layer Design for Secure and Resilient Cyber-Physical Systems: A Decision and Game Theoretic Approach 2020 ed. [Kõva köide]

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  • Formaat: Hardback, 212 pages, kõrgus x laius: 235x155 mm, kaal: 518 g, XVII, 212 p., 1 Hardback
  • Sari: Advances in Information Security 81
  • Ilmumisaeg: 17-Nov-2020
  • Kirjastus: Springer Nature Switzerland AG
  • ISBN-10: 3030602508
  • ISBN-13: 9783030602505
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Cross-Layer Design for Secure and Resilient Cyber-Physical Systems: A Decision and Game Theoretic Approach 2020 ed.Suurem pilt
  • Formaat: Hardback, 212 pages, kõrgus x laius: 235x155 mm, kaal: 518 g, XVII, 212 p., 1 Hardback
  • Sari: Advances in Information Security 81
  • Ilmumisaeg: 17-Nov-2020
  • Kirjastus: Springer Nature Switzerland AG
  • ISBN-10: 3030602508
  • ISBN-13: 9783030602505
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9783030602505.html
This book introduces a cross-layer design to achieve security and resilience for CPSs (Cyber-Physical Systems). The authors interconnect various technical tools and methods to capture the different properties between cyber and physical layers. Part II of this book bridges the gap between cryptography and control-theoretic tools. It develops a bespoke crypto-control framework to address security and resiliency in control and estimation problems where the outsourcing of computations is possible. Part III of this book bridges the gap between game theory and control theory and develops interdependent impact-aware security defense strategies and cyber-aware resilient control strategies.

With the rapid development of smart cities, there is a growing need to integrate the physical systems, ranging from large-scale infrastructures to small embedded systems, with networked communications. The integration of the physical and cyber systems forms Cyber-Physical Systems (CPSs), enabling the use of digital information and control technologies to improve the monitoring, operation, and planning of the systems. Despite these advantages, they are vulnerable to cyber-physical attacks, which aim to damage the physical layer through the cyber network.



This book also uses case studies from autonomous systems, communication-based train control systems, cyber manufacturing, and robotic systems to illustrate the proposed methodologies.  These case studies aim to motivate readers to adopt a cross-layer system perspective toward security and resilience issues of large and complex systems and develop domain-specific solutions to address CPS challenges.



A comprehensive suite of solutions to a broad range of technical challenges in secure and resilient control systems are described in this book (many of the findings in this book are useful to anyone working in cybersecurity). Researchers, professors, and advanced-level students working in computer science and engineering will find this book useful as a reference or secondary text. Industry professionals and military workers interested in cybersecurity will also want to purchase this book.
Part I Motivation and Framework
1 Introduction
3(6)
1.1 Cyber-Physical Systems and Smart Cities
3(1)
1.2 New Challenges in CPS
3(2)
1.3 Overview and Related Works
5(2)
1.4 Outline of the Book
7(2)
2 Cross-Layer Framework for CPSs
9(10)
2.1 Introduction to Cross-Layer Design
9(2)
2.2 Cross-Layer Design: Connecting Cryptography and Control Theory
11(1)
2.3 Cross-Layer Design: Connecting Game Theory with Control Theory
12(1)
2.4 Cross-Layer Design Under Incomplete Information
13(2)
2.5 Conclusions
15(4)
Part II Secure Outsourcing Computations of CPS
3 New Architecture: Cloud-Enabled CPS
19(6)
3.1 Promising Applications of CE-CPSs
19(4)
3.1.1 Cloud-Enabled Robotics
19(1)
3.1.2 Cloud-Enabled Smart Grids
20(1)
3.1.3 Cloud-Enabled Transport Systems
21(1)
3.1.4 Cloud-Enabled Manufacturing
22(1)
3.2 New Security Requirements of CE-CPSs
23(1)
3.3 Conclusions
23(2)
4 Secure and Resilient Design of Could-Enabled CPS
25(18)
4.1 New Challenges and Proposed Solutions of CE-CPS
25(2)
4.2 Problem Statements
27(1)
4.3 System Dynamics and MPC Algorithm
27(1)
4.4 The Standard Form of Quadratic Problem
28(1)
4.4.1 Cloud Attack Models
29(1)
4.4.2 The Framework of the Proposed Mechanism
29(1)
4.5 Confidentiality and Integrity
29(3)
4.5.1 Encryption Methods
30(1)
4.5.2 Verification Methods
31(1)
4.6 Availability Issues
32(3)
4.6.1 Switching Mode Mechanism
32(1)
4.6.2 Buffer Mode and Switching Condition
33(1)
4.6.3 The Local Controller for the Safe Mode
34(1)
4.7 Analysis and Experiments
35(5)
4.8 Conclusions and Notes
40(3)
5 Secure Data Assimilation of Cloud Sensor Networks
43(18)
5.1 Introduction to CE-LSNs
43(2)
5.2 Problem Formulation
45(2)
5.2.1 System Model and the Outsourcing Kalman Filter
45(1)
5.2.2 Challenges and Design Objectives
46(1)
5.3 The Secure Outsourcing Data Assimilation
47(4)
5.3.1 The Additive Homomorphic Encryption
47(1)
5.3.2 The Homomorphic Observer
48(1)
5.3.3 Customized Encryption for Outsourcing Computation
49(2)
5.4 Analysis of the Efficiency and Security
51(1)
5.4.1 Efficiency Analysis
52(1)
5.4.2 Security Analysis
52(1)
5.5 Analysis of Quantization Errors
52(2)
5.6 Experimental Results
54(3)
5.6.1 The Output of the Encrypted Information
55(1)
5.6.2 The Impact of the Quantization Errors
56(1)
5.7 Conclusions and Notes
57(4)
Part III Game-Theoretic Approach for CPS
6 Review of Game Theory
61(10)
6.1 Introduction to Game Theory
61(1)
6.2 Two-Person Zero-Sum Game Model
61(2)
6.2.1 Formulation of the Zero-Sum Game
62(1)
6.3 Stackelberg Game Model
63(1)
6.3.1 Formulation of the Stackelberg Game
63(1)
6.3.2 Security Design Based on Stackelberg Game
63(1)
6.4 Fliplt Game Model
64(3)
6.4.1 Formulation of Fliplt Game
65(1)
6.4.2 Analysis of the Fliplt Game
66(1)
6.5 Signaling Game with Evidence
67(2)
6.6 Conclusion and Notes
69(2)
7 A Game-Theoretic Approach to Secure Control of 3D Printers
71(20)
7.1 New Challenges in Networked 3D Printers
71(2)
7.2 Problem Formulation
73(6)
7.2.1 The Dynamic Model of 3D Printing Systems
73(2)
7.2.2 Physical Zero-Sum Game Framework
75(1)
7.2.3 A Cyber-Physical Attack Model for 3D-Printing Systems
76(1)
7.2.4 The Cyber Fliplt Game Model
77(1)
7.2.5 A Cyber-Physical Stackelberg Game Model
78(1)
7.3 Analysis of the Cyber-Physical Games
79(5)
7.3.1 Analysis of the Physical Zero-Sum Game Equilibrium
79(3)
7.3.2 Analysis of the Cyber Fliplt Game Equilibrium
82(1)
7.3.3 Analysis of the Cyber-Physical Stackelberg Game Equilibrium
82(2)
7.4 Numerical Results
84(5)
7.5 Conclusion and Notes
89(2)
8 A Game Framework to Secure Control of CBTC Systems
91(24)
8.1 Introduction to CBTC Systems
91(2)
8.2 Problem Formulation
93(5)
8.2.1 The Physical Model of a Train System
94(2)
8.2.2 Communication Model and Attack Model
96(2)
8.3 Estimation Approach and Security Criterion
98(3)
8.3.1 Physical Estimation Problem
98(1)
8.3.2 Security Criterion for CBTC System
99(2)
8.4 The Stochastic Game-Theoretic Framework
101(9)
8.4.1 Cyber Zero-Sum Game
101(2)
8.4.2 Analyzing the Equilibrium of the Game
103(3)
8.4.3 Special Case Study: Two-Channel Game
106(3)
8.4.4 Inter-Dependency Between Physical and Cyber Layers
109(1)
8.5 Experimental Results
110(3)
8.5.1 The Results of Cyber Layer
110(2)
8.5.2 The Results of Physical Layer
112(1)
8.6 Conclusions and Notes
113(2)
9 Secure Estimation of CPS with a Digital Twin
115(24)
9.1 Using Digital Twin to Enhance Security Level in CPS
115(2)
9.2 System Modelling and Characterization
117(7)
9.2.1 System Model and Control Problem of a CPS
118(1)
9.2.2 Kalman Filter Problem
119(1)
9.2.3 Stealthy Estimation Attack
120(1)
9.2.4 Digital Twin for the CPS
121(2)
9.2.5 General Setup of Signaling Game with Evidence
123(1)
9.3 Equilibrium Results of the Cyber SGE
124(8)
9.3.1 SGE Setup for the CPSs
125(1)
9.3.2 Best Response of the Players and a PBNE of the SGE
126(4)
9.3.3 Estimated Loss Under the Stealthy Attack
130(2)
9.4 Simulation Results
132(4)
9.4.1 Experimental Setup
133(3)
9.5 Conclusions and Notes
136(3)
10 Introduction to Partially Observed MDPs
139(8)
10.1 Preliminaries of POMDPs
139(3)
10.1.1 Definition of a POMDP
139(2)
10.1.2 Belief State Formulation of a POMDP
141(1)
10.1.3 Stochastic Dynamic Programming
142(1)
10.2 Algorithms for Infinite Horizon POMDPs
142(3)
10.2.1 Piecewise Linear Property of POMDPs
143(1)
10.2.2 Algorithms Based on Markov Partition
143(2)
10.3 Conclusions and Notes
145(2)
11 Secure and Resilient Control of ROSs
147(32)
11.1 New Challenges in Networked ROS s
147(2)
11.2 Problem Formulation
149(8)
11.2.1 The Outline of the Proposed Mechanism
149(1)
11.2.2 The Physical Dynamics of a ROS Agent
150(1)
11.2.3 Attack Model: Data-Integrity Attack
151(1)
11.2.4 The Lightweight MAC and the Estimated Delay
152(1)
11.2.5 Physical-Aware Design of the Key Length
153(1)
11.2.6 Cyber States and Cyber Actions
154(1)
11.2.7 Stochastic Cyber Markov Decision Process
155(2)
11.3 Cyber POMDP Formulation for ROSs
157(8)
11.3.1 Basic Setups of the Cyber POMDP
157(2)
11.3.2 Main Results of Cyber POMDP
159(3)
11.3.3 Special Case of the Cyber POMDP
162(3)
11.4 Experimental Results
165(7)
11.4.1 Part I: Physical Performance
166(1)
11.4.2 Part II: Cyber Performance
167(5)
11.5 Conclusions and Notes
172(7)
Part IV Discussion of the Future Work
12 Future Work in Security Design of CPSs
179(6)
12.1 Research Directions: Advanced Attack Models
179(2)
12.1.1 Man-in-the-Middle Attack
179(1)
12.1.2 Compromised-Key Attack
180(1)
12.2 Research Directions: Data-Availability Issues in CPSs
181(2)
12.2.1 Safe-Mode Mechanism
181(1)
12.2.2 Availability of a Partially Compromised System
182(1)
12.3 Conclusions
183(2)
A Basics of Optimization
185(6)
A.1 Optimality Conditions for Unconstrained Problems
186(1)
A.2 Optimality Conditions for Constrained Problems
186(5)
B Basics of Linear-Quadratic Optimal Control
191(8)
B.1 Finite-Time Optimal Control Problem Formulation
191(1)
B.2 Infinite Horizon Optimal Control Problem Formulation
192(1)
B.3 Principle of Optimality
193(1)
B.4 Finite-Time Linear-Quadratic Optimal Control
194(3)
B.5 Infinite-Time Linear-Quadratic Optimal Control
197(2)
References 199(12)
Index 211
Quanyan Zhu received B. Eng. in Honors Electrical Engineering from McGill University in 2006, M. A. Sc. from the University of Toronto in 2008, and Ph.D. from the University of Illinois at Urbana-Champaign (UIUC) in 2013. After stints at Princeton University, he is currently an associate professor at the Department of Electrical and Computer Engineering, New York University (NYU). He is an affiliated faculty member of the Center for Urban Science and Progress (CUSP) at NYU. He is a recipient of many awards, including NSF CAREER Award, NYU Goddard Junior Faculty Fellowship, NSERC Postdoctoral Fellowship (PDF), NSERC Canada Graduate Scholarship (CGS), and Mavis Future Faculty Fellowships. He spearheaded and chaired INFOCOM Workshop on Communications and Control on Smart Energy Systems (CCSES), Midwest Workshop on Control and Game Theory (WCGT), and ICRA workshop on Security and Privacy of Robotics. His current research interests include game theory, machine learning, cyber deception, network optimization and control, smart cities, Internet of Things, and cyber-physical systems. He has served as the general chair or the TPC chair of the 7th and the 11th Conference on Decision and Game Theory for Security (GameSec) in 2016 and 2020, the 9th International Conference on NETwork Games, COntrol and OPtimisation (NETGCOOP) in 2018, the 5th International Conference on Artificial Intelligence and Security (ICAIS 2019) in 2019, and 2020 IEEE Workshop on Information Forensics and Security (WIFS). He has also spearheaded in 2020 the IEEE Control System Society (CSS) Technical Committee on Security, Privacy, and Resilience. He is a co-author of two recent books published by Springer: Cyber-Security in Critical Infrastructures: A Game-Theoretic Approach (with S. Rass, S. Schauer, and S. König) and A Game- and Decision-Theoretic Approach to Resilient Interdependent Network Analysis and Design (with J. Chen). Zhiheng Xu received his Ph.D. degree in Electrical Engineering from New York University in 2018. After his Ph.D. graduation, he went to Nanyang Technological University, Singapore, working as Research Fellow for two years. Currently, he works as a senior robotics software engineer at the Department of Intelligent Machines, Dyson Company. His research interests include cyber-physical security, artificial intelligence, reinforcement learning, intelligent decision making, and game theory