UNIVERSITY of CALIFORNIA SAN DIEGO Communication and Security in Cyber-Physical Systems a Dissertation Submitted in Partial Sati
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UNIVERSITY OF CALIFORNIA SAN DIEGO Communication and security in cyber-physical systems A dissertation submitted in partial satisfaction of the requirements for the degree Doctor of Philosophy in Electrical Engineering (Intelligent Systems, Robotics, and Control) by Mohammad Javad Khojasteh Committee in charge: Professor Massimo Franceschetti, Chair Professor Jorge Cortes´ Professor Tara Javidi Professor Sonia Mart´ınez Professor Alon Orlitsky 2019 Copyright Mohammad Javad Khojasteh, 2019 All rights reserved. The dissertation of Mohammad Javad Khojasteh is approved, and it is acceptable in quality and form for publication on microfilm and electronically: Chair University of California San Diego 2019 iii DEDICATION To Sogoli iv EPIGRAPH Dr. Ford: You think it’s sabotage? Imagine someone’s been diddling with our creations? Bernard: It’s the simplest solution. Dr. Ford: Ah, Mr. Occam’s razor. The problem, Bernard, is that what you and I do is so complicated. We practice witchcraft. We speak the right words. Then we create life itself out of chaos. William of Occam was a 13th century monk. He can’t help us now, Bernard. He would have us burned at the stake. Westworld, Chestnut v TABLE OF CONTENTS Signature Page . iii Dedication . iv Epigraph . iv Table of Contents . vi List of Figures . ix List of Tables . xi Acknowledgements . xii Vita ............................................. xiv Abstract of the Dissertation . xv Chapter 1 Introduction . .1 1.1 Communication . .2 1.2 Security . .4 1.3 Dissertation Overview . .7 1.4 Notation . .9 Chapter 2 The value of timing information in event-triggered control . 12 2.1 Introduction . 12 2.2 Problem formulation . 15 2.2.1 System model . 15 2.2.2 Triggering strategy and controller dynamics . 16 2.2.3 Information transmission rate . 19 2.2.4 Information access rate . 21 2.3 Necessary condition on the access rate . 22 2.4 Necessary and sufficient conditions on the transmission rate . 25 2.4.1 Necessary condition on the transmission rate . 26 2.4.2 Phase transition behavior . 32 2.4.3 Sufficient condition on the transmission rate . 36 2.4.4 Simulation . 44 2.5 Extension to vector systems . 47 2.6 Time-triggering versus event-triggering control over communication channels . 60 2.7 Conclusions . 66 vi Chapter 3 Event-triggered stabilization over digital channels of systems with disturbances 68 3.1 Introduction . 68 3.2 Problem formulation . 72 3.3 Event-triggered design . 75 3.4 Sufficient and necessary conditions on the information transmission rate 79 3.4.1 Sufficient information transmission rate . 79 3.4.2 Necessary information transmission rate . 85 3.5 Extension to complex linear systems . 93 3.5.1 Event-triggered control for complex linear systems . 95 3.5.2 Sufficient information transmission rate . 96 3.6 Simulations . 102 3.6.1 Event-triggered control of diagonalizable systems with real eigenvalues . 102 3.6.2 Event-triggered control of complex systems . 107 3.7 Implementation . 108 3.7.1 Plant Dynamics . 109 3.7.2 Implementation and System Architecture . 111 3.7.3 Experimental results . 112 3.8 Extension to nonlinear systems . 114 3.9 Simulations for nonlinear systems . 124 3.10 Conclusion . 126 Chapter 4 Stabilizing a linear system using phone calls . 128 4.1 Introduction . 128 4.2 System and channel model . 132 4.2.1 The channel . 133 4.2.2 Source-channel encoder . 133 4.2.3 Anytime decoder . 134 4.2.4 Capacity of the channel . 135 4.3 Main results . 136 4.3.1 Necessary condition . 136 4.3.2 Sufficient condition . 137 4.4 The estimation problem . 138 4.4.1 Necessary condition . 138 4.4.2 Sufficient condition . 140 4.5 The stabilization problem . 141 4.5.1 Necessary condition . 141 4.5.2 Sufficient condition . 142 4.6 Comparison with previous work . 147 4.6.1 Comparison with stabilization over the erasure channel . 147 4.6.2 Comparison with event triggering strategies . 148 4.7 Numerical example . 149 4.8 Conclusions . 153 vii 4.9 Appendix: proofs of the estimation results . 155 4.9.1 Proof of Theorem 16 . 155 4.9.2 Proof of Theorem 17 . 161 Chapter 5 Learning-based attacks in cyber-physical systems . 171 5.1 Problem Setup . 174 5.1.1 Learning-based attacks . 176 5.1.2 Detection . 176 5.1.3 Performance Measures . 178 5.2 Statement of the results . 179 5.2.1 Lower Bound on the Deception Probability . 180 5.2.2 Upper Bound on the Deception Probability . 185 5.2.3 Privacy-enhancing signal . 190 5.3 Extension to vector systems . 193 5.3.1 Lower Bound on the Deception Probability . 197 5.4 Exploration vs. Exploitation . 205 5.4.1 Main results . 206 5.5 Conclusions . 220 Bibliography . 221 viii LIST OF FIGURES Figure 1.1: Cyber-physical systems . .1 Figure 1.2: Cloud robots and automation systems . .2 Figure 1.3: Dynamical system abstraction of CPS and cloud robots . .3 Figure 1.4: Representation of information transmission using data payload and transmis- sion time of the packet in a digital channel . .3 Figure 1.5: Architecture and components of the prototype. .4 Figure 1.6: Physical security in CPS . .5 Figure 1.7: The man in the middle attack . .5 Figure 2.1: System model . 15 Figure 2.2: Evolution of the state estimation error . 20 Figure 2.3: The phase transition behavior . 33 Figure 2.4: Illustration of the phase transition behavior for different values of ρ0 .... 34 Figure 2.5: Comparison between the sufficient and necessary conditions . 43 Figure 2.6: Illustration of the sufficient transmission rate versus the upper bound of delay for different values of ρ0 ........................... 44 Figure 2.7: An example realization of our design . 45 Figure 2.8: Information transmission rate in simulations versus the upper bound of the delay in the communication channel . 46 Figure 2.9: Time-triggering versus event-triggering control over communication channels 65 Figure 3.1: The inverted pendulum prototype . 71 Figure 3.2: The encoding-decoding algorithms in the proposed event-triggered control scheme . 81 Figure 3.3: Illustration of the sufficient and necessary transmission rates as functions of the delay upper bound . 93 Figure 3.4: The evolution of the state estimation error before and after an event . 96 Figure 3.5: Sufficient information transmission rate as a function of channel delay upper bound . 101 Figure 3.6: A pendulum mounted on a cart . 103 Figure 3.7: Simulation results . 106 Figure 3.8: Information transmission rate in simulations . 107 Figure 3.9: Simulation results . 108 Figure 3.10: Information transmission rate in experiments compared with the entropy rate of the system . 114 Figure 3.11: Experimental results for stabilizing the inverted pendulum over a digital channel with random upper bounded delay . 115 Figure 3.12: Robustness of the event-triggered control strategy against additional distur- bances. 115 Figure 3.13: Simulation results for stabilization of the nonlinear plant . 124 Figure 3.14: Information transmission rate in simulations for the nonlinear plant . 125 ix Figure 4.1: Model of a networked control system where the feedback loop is closed over a timining channel . 132 Figure 4.2: The timing channel . 134 Figure 4.3: The estimation.