Autonomous Cyber Resilience

Charles A. Kamhoua, Ph.D., is a Researcher at the DEVCOM Army Research Laboratory Network Security Branch. Alexander Kott, Ph.D., is the Chief Scientist at the DEVCOM Army Research Laboratory. Quanyan Zhu, Ph.D., is an Associate Professor in the Department of Electrical and Computer Engineering at New York University. Nandi O. Leslie, Ph.D., is a Principal Technical Fellow in Raytheon Engineering at RTX.

• Preface xvEditor Biographies xvii1 Introduction 1Alexander Kott1.1 Cyber Resilience and Cybersecurity 11.2 Autonomy and Cyber Resilience 31.3 Autonomous Actions 41.4 Approaches to Implementing Autonomous Cyber Resilience 51.5 Benefits and Risks of Autonomous Cyber Resilience 81.6 The Preview of the Book 9Part 1 Cyber Resilience 132 Game-theoretic Foundations for Cyber Resilience Against Deceptive Information Attacks in Intelligent Transportation Systems 15Ya-Ting Yang and Quanyan Zhu2.1 Introduction 152.2 Deceptive Information Attacks 192.3 Cross-layer Resilience 292.4 Case Study 352.5 Conclusion and Discussion 433 CYBER-MIRA: Cyber Mission Impact Resilience Assessment Framework for Tactical Mission Systems 53Ashrith Reddy Thukkaraju, Han Jun Yoon, Shou Matsumoto, Jair Feldens Ferrari, Donghwan Lee, Myung Kil Ahn, Paulo Costa, and Jin-Hee Cho3.1 Introduction 533.2 Related Work 563.3 System Model 593.4 CYBER-MIRA Framework 643.5 Limitations 863.6 Conclusion and Future Work 864 Modeling Autonomous Network Resilience in Adversarial Environments Using Machine Learning and Topological Data Analysis 91Nandi O. Leslie4.1 Introduction 914.2 TDA Concepts 934.3 Network Resilience Modeling 974.4 Conclusion 1015 Game-theoretic Frameworks for Zero-trust Authentication in Autonomous Cyber Resilience 105Yunfei Ge and Quanyan Zhu5.1 Introduction 1055.2 From Traditional Security to Zero Trust 1085.3 Trust Evaluation Design 1105.4 Policy Engine Design 1165.5 Zero Trust for Cyber Resilience 1185.6 Strategic Zero-trust Implementation 1235.7 Conclusion 1326 Cyber Insurance for Cyber Resilience 139Shutian Liu and Quanyan Zhu6.1 Introduction 1396.2 Attack Models and Insured Targets 1446.3 Defense Mechanisms and Residual Risks 1496.4 Insurer's Observations and the P-A Model 1556.5 Modeling of Risk Preferences 1586.6 Insurance Design with Preference Manipulation 1626.7 Dynamic Insurances 1646.8 Regulations on Cyber Insurance 1666.9 Conclusion 1707 Enhancing Cyber Resiliency: Assessing the Effectiveness of Deploying Honeypots in Different Network Topologies 1837.1 Introduction 1837.2 Task Description 1857.3 A Cognitive Model of Attackers in HackIT 1937.4 Discussion 199Part 2 Resilient Machine Learning 2038 Computational Game Theory for Security 205Yevgeniy Vorobeychik8.1 Introduction 2058.2 Stackelberg Games 2068.3 Stackelberg Security Games 2098.4 Security Games on Networks 2128.5 Stochastic Stackelberg Games and Adversarial Patrolling 2158.6 Conclusion 2219 Privacy and Robustness Trade-offs of Artificial Intelligence Models with Federated Learning 225Kemal Davaslioglu, Yi Shi, and Yalin E. Sagduyu9.1 Introduction 2259.2 Model Inversion Attacks 2299.3 Membership Inference Attacks 2439.4 Federated Learning 2649.5 Discussion 2759.6 Conclusions 2769.7 Acknowledgment 27710 Resilient Deep Neural Network Random Ensemble Against Adversarial Attacks 281Kirsen Sullivan, Yitao Li, Charles A. Kamhoua, and Bowei xi10.1 Introduction 28110.2 Data and Bootstrapped CNNs 28410.3 Bootstrapped Distributions 29010.4 Randomized DNN Ensembles with Gaussian Random Weights 30010.5 Ensemble Experiment Results 30210.6 Conclusion 311Part 3 Game Theory for Network Resilience 31711 Poisoning Attack and Defense Game for Federated Learning in Resilient NextG Networks 319Yalin E. Sagduyu, Tugba Erpek, and Yi Shi11.1 Introduction 31911.2 Federated Learning for Distributed Spectrum Monitoring 32311.3 Attack and Defense Mechanisms for Resilient Federated Learning 32511.4 Poisoning Attack–Defense Game for Two Clients 33011.5 Poisoning Attack–Defense Game for More than Two Clients 33711.6 Future Research Directions 33811.7 Conclusion 34112 Self-adapting Quantum Network Provisioning Using Game Theory 347Stefan Rass, Miralem Mehic, Sandra König, Stefan Schauer, and Miroslav Voznak12.1 Introduction 34712.2 Basics of Quantum Networks 34812.3 Game Theory to Orchestrate Cryptography 34912.4 Self-adaption of QKD Devices to Environmental Conditions 36112.5 Adapting the Level of Service to Traffic Changes 36912.6 Adapting the Network Topology 37212.7 Conclusions, Outlook, and QKD in Today's Networks 37613 Conclusion and Future Works 383Quanyan Zhu13.1 Overview 38313.2 Summary 38413.3 Future Directions: Charting the Path Toward Autonomous Cyber Resilience 39613.4 Concluding Remarks 404Index 407