Adaptive Strategic Cyber Defense for Advanced Persistent Threats in Critical Infrastructure Networks

Chen

National Science Review

et al. 2020

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Modern control systems are featured by their hierarchical structure composing of cyber, physical, and human layers. The intricate dependencies among multiple layers and units of modern control systems require an integrated framework to address cross-layer design issues related to security and resilience challenges. To this end, game theory provides a bottom-up modeling paradigm to capture the strategic interactions among multiple components of the complex system and enables a holistic view to understand and design cyber-physical-human control systems. In this review, we first provide a multi-layer perspective toward increasingly complex and integrated control systems and then introduce several variants of dynamic games for modeling different layers of control systems. We present game-theoretic methods for understanding the fundamental tradeoffs of robustness, security, and resilience and developing a cross-layer approach to enhance the system performance in various adversarial environments. This review also includes three quintessential research problems that represent three research directions where dynamic game approaches can bridge between multiple research areas and make significant contributions to the design of modern control systems. The paper is concluded with a discussion on emerging areas of research that crosscut dynamic games and control systems.

Section: B Game-theoretic Methodsmentioning

confidence: 99%

Dynamic games for secure and resilient control system design

Chen

National Science Review

et al. 2020

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“…Game-theoretic models are natural frameworks to capture the multistage interaction between attackers and defenders. Recently, game theory has been applied to different sets of security problems, e.g., Stackelberg and signaling games for deception and proactive defenses [21,6,22,23,24,16,25,26,27], network games for cyber-physical security [28,29,30,31,32,33,34,35,36,37], dynamic games for adaptive defense [38,39,40,41,3,42,43,44,45,46], and mechanism design theory for security [47,48,49,50,51,52,53,54,55].…”

Section: Literaturementioning

confidence: 99%

“…In this chapter, we illustrate three active defense schemes in our previous works, which are designed based on the new cyber security principle. They are defensive deception for detection and counter-deception [3,4,5] in Section 2, feedback-driven Moving Target Defense (MTD) [6] in Section 3, and adaptive honeypot engagement [7] in Section 4. All three schemes is of incomplete information, and we arrange them based on three progressive levels of information restrictions as shown in the left part of Fig.…”

Section: Introductionmentioning

confidence: 99%

Strategic Learning for Active, Adaptive, and Autonomous Cyber Defense

Adaptive Autonomous Secure Cyber Systems

Zhu

2020

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The increasing instances of advanced attacks call for a new defense paradigm that is active, autonomous, and adaptive, named as the '3A' defense paradigm. This chapter introduces three defense schemes that actively interact with attackers to increase the attack cost and gather threat information, i.e., defensive deception for detection and counter-deception, feedback-driven Moving Target Defense (MTD), and adaptive honeypot engagement. Due to the cyber deception, external noise, and the absent knowledge of the other players' behaviors and goals, these schemes possess three progressive levels of information restrictions, i.e., from the parameter uncertainty, the payoff uncertainty, to the environmental uncertainty. To estimate the unknown and reduce the uncertainty, we adopt three different strategic learning schemes that fit the associated information restrictions. All three learning schemes share the same feedback structure of sensation, estimation, and actions so that the most rewarding policies get reinforced and converge to the optimal ones in autonomous and adaptive fashions. This work aims to shed lights on proactive defense strategies, lay a solid foundation for strategic learning under incomplete information, and quantify the tradeoff between the security and costs.Recent instances of WannaCry ransomware, Petya cyberattack, and Stuxnet malware have demonstrated the trends of modern attacks and the corresponding new security challenges as follows.

Sensors and Systems for Space Applications XII

“…On one hand, NoN improves the system dependability and interoperablity [29]. On the other hand, the network interdependency introduces new challenges for the system operator to maintain the NoN performance as the interconnection provides extra opportunity for the propagation of attacks from one network to another, e.g., through lateral movement in advanced persistent threat (APT) [30]. Traditional defensive strategies for networked systems are no longer sufficient in this emerging NoN framework.…”

Section: Introductionmentioning

confidence: 99%

“…Related Work: Game-theoretic approaches have been extensively adopted for resilient control of networked system and critical infrastructures [1], [7], [34], [37], [39], [40]. To analyze strategic interactions between attackers and defenders, a large number of works have focused on the security modeling and design through game-theoretic frameworks [23], [30], [35], [36], [38], [41]. Furthermore, researchers have also used game-theoretic methods to enable decentralized multi-layer network/network-of-networks design [29], [32], [42], [43].…”

Section: Introductionmentioning

confidence: 99%

A games-in-games approach to mosaic command and control design of dynamic network-of-networks for secure and resilient multi-domain operations

Chen

Zhu

2019

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This paper presents a games-in-games approach to provide design guidelines for mosaic command and control that enables the secure and resilient multi-domain operations. Under the mosaic design, pieces or agents in the network are equipped with flexible interoperability and the capability of self-adaptability, self-healing, and resiliency so that they can reconfigure their responses to achieve the global mission in spite of failures of nodes and links in the adversarial environment. The proposed games-in-games approach provides a system-of-systems science for mosaic distributed design of large-scale systems.Specifically, the framework integrates three layers of design for each agent including strategic layer, tactical layer, and mission layer. Each layer in the established model corresponds to a game of a different scale that enables the integration of threat models and achieve self-mitigation and resilience capabilities.The solution concept of the developed multi-layer multi-scale mosaic design is characterized by Gestalt Nash equilibrium (GNE) which considers the interactions between agents across different layers. The developed approach is applicable to modern battlefield networks which are composed of heterogeneous assets that access highly diverse and dynamic information sources over multiple domains. By leveraging mosaic design principles, we can achieve the desired operational goals of deployed networks in a case study and ensure connectivity among entities for the exchange of information to accomplish the mission.