Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
153 tokens/sec
GPT-4o
7 tokens/sec
Gemini 2.5 Pro Pro
45 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
38 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Symbiotic Game and Foundation Models for Cyber Deception Operations in Strategic Cyber Warfare (2403.10570v2)

Published 14 Mar 2024 in cs.CR, cs.AI, and cs.GT

Abstract: We are currently facing unprecedented cyber warfare with the rapid evolution of tactics, increasing asymmetry of intelligence, and the growing accessibility of hacking tools. In this landscape, cyber deception emerges as a critical component of our defense strategy against increasingly sophisticated attacks. This chapter aims to highlight the pivotal role of game-theoretic models and foundation models (FMs) in analyzing, designing, and implementing cyber deception tactics. Game models (GMs) serve as a foundational framework for modeling diverse adversarial interactions, allowing us to encapsulate both adversarial knowledge and domain-specific insights. Meanwhile, FMs serve as the building blocks for creating tailored machine learning models suited to given applications. By leveraging the synergy between GMs and FMs, we can advance proactive and automated cyber defense mechanisms by not only securing our networks against attacks but also enhancing their resilience against well-planned operations. This chapter discusses the games at the tactical, operational, and strategic levels of warfare, delves into the symbiotic relationship between these methodologies, and explores relevant applications where such a framework can make a substantial impact in cybersecurity. The chapter discusses the promising direction of the multi-agent neurosymbolic conjectural learning (MANSCOL), which allows the defender to predict adversarial behaviors, design adaptive defensive deception tactics, and synthesize knowledge for the operational level synthesis and adaptation. FMs serve as pivotal tools across various functions for MANSCOL, including reinforcement learning, knowledge assimilation, formation of conjectures, and contextual representation. This chapter concludes with a discussion of the challenges associated with FMs and their application in the domain of cybersecurity.

Definition Search Book Streamline Icon: https://streamlinehq.com
References (110)
  1. Autonomous cyber deception. Springer, 2019.
  2. A. H. Anwar and C. Kamhoua. Game theory on attack graph for cyber deception. In International Conference on Decision and Game Theory for Security, pages 445–456. Springer, 2020.
  3. Causality and batch reinforcement learning: Complementary approaches to planning in unknown domains. arXiv preprint arXiv:2006.02579, 2020.
  4. P. G. Bennett. Hypergames: developing a model of conflict. Futures, 12(6):489–507, 1980.
  5. Honeypot type selection games for smart grid networks. In Decision and Game Theory for Security: 10th International Conference, GameSec 2019, Stockholm, Sweden, October 30–November 1, 2019, Proceedings 10, pages 85–96. Springer, 2019.
  6. Defending against the unknown enemy: Applying flipit to system security. In International Conference on Decision and Game Theory for Security, pages 248–263. Springer, 2012.
  7. A behavioral approach to repeated bayesian security games. The Annals of Applied Statistics, 18(1):199–223, 2024.
  8. Compliance signaling games: toward modeling the deterrence of insider threats. Computational and Mathematical Organization Theory, 22:318–349, 2016.
  9. Compliance control: Managed vulnerability surface in social-technological systems via signaling games. In Proceedings of the 7th ACM CCS international workshop on managing insider security threats, pages 53–62, 2015.
  10. Decision-theoretic and game-theoretic approaches to it security investment. Journal of Management Information Systems, 25(2):281–304, 2008.
  11. A dynamic game analysis and design of infrastructure network protection and recovery: 125. ACM SIGMETRICS Performance Evaluation Review, 45(2):128, 2017.
  12. A dynamic game approach to strategic design of secure and resilient infrastructure network. IEEE Transactions on Information Forensics and security, 15:462–474, 2019.
  13. Optimal secure two-layer iot network design. IEEE Transactions on Control of Network Systems, 7(1):398–409, 2020.
  14. J. Chen and Q. Zhu. A linear quadratic differential game approach to dynamic contract design for systemic cyber risk management under asymmetric information. In 2018 56th Annual Allerton Conference on Communication, Control, and Computing (Allerton), pages 575–582. IEEE, 2018.
  15. J. Chen and Q. Zhu. Security investment under cognitive constraints: A gestalt nash equilibrium approach. In 2018 52nd Annual Conference on Information Sciences and Systems (CISS), pages 1–6. IEEE, 2018.
  16. J. Chen and Q. Zhu. A game-and decision-theoretic approach to resilient interdependent network analysis and design. Springer, 2019.
  17. J. Chen and Q. Zhu. Interdependent strategic security risk management with bounded rationality in the internet of things. IEEE Transactions on Information Forensics and Security, 14(11):2958–2971, 2019.
  18. J. Chen and Q. Zhu. A system-of-systems approach to strategic cyber-defense and robust switching control design for cyber-physical wind energy systems. In Security and Resilience of Control Systems: Theory and Applications, pages 177–202. Springer, 2022.
  19. Dynamic contract design for systemic cyber risk management of interdependent enterprise networks. Dynamic Games and Applications, 11:294–325, 2021.
  20. Decision transformer: Reinforcement learning via sequence modeling. In M. Ranzato, A. Beygelzimer, Y. Dauphin, P. Liang, and J. W. Vaughan, editors, Advances in Neural Information Processing Systems, volume 34, pages 15084–15097. Curran Associates, Inc., 2021.
  21. Deceptive routing in relay networks. In Decision and Game Theory for Security: Third International Conference, GameSec 2012, Budapest, Hungary, November 5-6, 2012. Proceedings 3, pages 171–185. Springer, 2012.
  22. Simple and controllable music generation. Advances in Neural Information Processing Systems, 36, 2024.
  23. Vwc-bert: Scaling vulnerability–weakness–exploit mapping on modern ai accelerators. In 2022 IEEE International Conference on Big Data (Big Data), pages 1224–1229, 2022.
  24. I. Esponda and D. Pouzo. Berk–nash equilibrium: A framework for modeling agents with misspecified models. Econometrica, 84(3):1093–1130, 2016.
  25. Stealthy attacks meets insider threats: A three-player game model. In MILCOM 2015-2015 IEEE Military Communications Conference, pages 25–30. IEEE, 2015.
  26. D. Fudenberg and D. K. Levine. Self-Confirming Equilibrium. Econometrica, 61(3):523, 1993.
  27. Smurfen: A system framework for rule sharing collaborative intrusion detection. In 2011 7th International Conference on Network and Service Management, pages 1–6. IEEE, 2011.
  28. Scenario-Agnostic Zero-Trust Defense with Explainable Threshold Policy: A Meta-Learning Approach. IEEE INFOCOM 2023 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), 00:1–6, 2023.
  29. Y. Ge and Q. Zhu. Mufaza: Multi-source fast and autonomous zero-trust authentication for 5g networks. In MILCOM 2022-2022 IEEE Military Communications Conference (MILCOM), pages 571–576. IEEE, 2022.
  30. Y. Ge and Q. Zhu. Gazeta: Game-theoretic zero-trust authentication for defense against lateral movement in 5g iot networks. IEEE Transactions on Information Forensics and Security, 2023.
  31. R. Golman and S. E. Page. General blotto: games of allocative strategic mismatch. Public Choice, 138:279–299, 2009.
  32. Cve2att&ck: Bert-based mapping of cves to mitre att&ck techniques. Algorithms, 15(9), 2022.
  33. J. Grossklags and B. Johnson. Uncertainty in the weakest-link security game. In 2009 International Conference on Game Theory for Networks, pages 673–682. IEEE, 2009.
  34. Game theory-based authentication framework to secure internet of vehicles with blockchain. Sensors, 22(14):5119, 2022.
  35. Automated security response through online learning with adaptive conjectures. arXiv preprint arXiv:2402.12499, 2024.
  36. J. C. Harsanyi. Games with incomplete information played by “bayesian” players part ii. bayesian equilibrium points. Management science, 14(5):320–334, 1968.
  37. J. C. Harsanyi. Games with incomplete information. The American Economic Review, 85(3):291–303, 1995.
  38. S. Hart. Discrete colonel blotto and general lotto games. International Journal of Game Theory, 36(3-4):441–460, 2008.
  39. Manipulating adversary’s belief: A dynamic game approach to deception by design for proactive network security. In Decision and Game Theory for Security: 8th International Conference, GameSec 2017, Vienna, Austria, October 23-25, 2017, Proceedings, pages 273–294. Springer, 2017.
  40. Y. Hu and Q. Zhu. Evasion-aware neyman-pearson detectors: A game-theoretic approach. In 2022 IEEE 61st Conference on Decision and Control (CDC), pages 6111–6117. IEEE, 2022.
  41. A large-scale markov game approach to dynamic protection of interdependent infrastructure networks. In International Conference on Decision and Game Theory for Security, pages 357–376. Springer, 2017.
  42. Factored markov game theory for secure interdependent infrastructure networks. Game Theory for Security and Risk Management: From Theory to Practice, pages 99–126, 2018.
  43. Advert: an adaptive and data-driven attention enhancement mechanism for phishing prevention. IEEE Transactions on Information Forensics and Security, 17:2585–2597, 2022.
  44. L. Huang and Q. Zhu. Adaptive honeypot engagement through reinforcement learning of semi-markov decision processes. In Decision and Game Theory for Security: 10th International Conference, GameSec 2019, Stockholm, Sweden, October 30–November 1, 2019, Proceedings 10, pages 196–216. Springer, 2019.
  45. L. Huang and Q. Zhu. Dynamic bayesian games for adversarial and defensive cyber deception. Autonomous Cyber Deception: Reasoning, Adaptive Planning, and Evaluation of HoneyThings, pages 75–97, 2019.
  46. L. Huang and Q. Zhu. A dynamic games approach to proactive defense strategies against advanced persistent threats in cyber-physical systems. Computers & Security, 89:101660, 2020.
  47. L. Huang and Q. Zhu. Duplicity games for deception design with an application to insider threat mitigation. IEEE Transactions on Information Forensics and Security, 16:4843–4856, 2021.
  48. Defending an asset with partial information and selected observations: A differential game framework. In 2021 60th IEEE Conference on Decision and Control (CDC), pages 2366–2373. IEEE, 2021.
  49. Continuous-time markov decision processes with controlled observations. In 2019 57th Annual Allerton Conference on Communication, Control, and Computing (Allerton), pages 32–39. IEEE, 2019.
  50. Y. Huang and Q. Zhu. A pursuit-evasion differential game with strategic information acquisition. arXiv preprint arXiv:2102.05469, 2021.
  51. Cyber deception. Cham, Switzerland: Springer, 2016.
  52. Offline reinforcement learning as one big sequence modeling problem. Advances in neural information processing systems, 34:1273–1286, 2021.
  53. Game theory and machine learning for cyber security. John Wiley & Sons, 2021.
  54. A game theoretic model for enabling honeypots in iot networks. In 2016 IEEE International Conference on Communications (ICC), pages 1–6. IEEE, 2016.
  55. Deceptive attack and defense game in honeypot-enabled networks for the internet of things. IEEE Internet of Things Journal, 3(6):1025–1035, 2016.
  56. Flipthem: Modeling targeted attacks with flipit for multiple resources. In Decision and Game Theory for Security: 5th International Conference, GameSec 2014, Los Angeles, CA, USA, November 6-7, 2014. Proceedings 5, pages 175–194. Springer, 2014.
  57. Self-Confirming Transformer for Locally Consistent Online Adaptation in Multi-Agent Reinforcement Learning. arXiv, 2023.
  58. Conjectural online learning with first-order beliefs in asymmetric information stochastic games. arXiv preprint arXiv:2402.18781, 2024.
  59. Self-Adaptive Driving in Nonstationary Environments through Conjectural Online Lookahead Adaptation. 2023 IEEE International Conference on Robotics and Automation (ICRA), 00:7205–7211, 2023.
  60. Decision-Dominant Strategic Defense Against Lateral Movement for 5G Zero-Trust Multi-Domain Networks. arXiv preprint arXiv:2310.01675, 2023.
  61. Blackwell Online Learning for Markov Decision Processes. 2021 55th Annual Conference on Information Sciences and Systems (CISS), 00:1–6, 2021.
  62. The Confluence of Networks, Games, and Learning a Game-Theoretic Framework for Multiagent Decision Making Over Networks. IEEE Control Systems, 42(4):35–67, 2022.
  63. The role of information structures in game-theoretic multi-agent learning. Annual Reviews in Control, 53:296–314, 2022.
  64. T. Li and Q. Zhu. On the Price of Transparency: A Comparison Between Overt Persuasion and Covert Signaling. 2023 62nd IEEE Conference on Decision and Control (CDC), 00:4267–4272, 2023.
  65. Game-theoretic modeling and analysis of insider threats. International Journal of Critical Infrastructure Protection, 1:75–80, 2008.
  66. Game-Theoretic Distributed Empirical Risk Minimization With Strategic Network Design. IEEE Transactions on Signal and Information Processing over Networks, 9:542–556, 2023.
  67. S. Liu and Q. Zhu. Information manipulation in partially observable markov decision processes. arXiv preprint arXiv:2312.07862, 2023.
  68. Game theory meets network security and privacy. ACM Computing Surveys (CSUR), 45(3):1–39, 2013.
  69. Game Theory. Cambridge University Press, Cambridge, 2020.
  70. J. Nash. Two-person cooperative games. Econometrica: Journal of the Econometric Society, pages 128–140, 1953.
  71. Subgame perfect equilibrium analysis for jamming attacks on resilient graphs. In 2019 American Control Conference (ACC), pages 2060–2065. IEEE, 2019.
  72. OpenAI. GPT-4 technical report, 2023.
  73. A First Order Meta Stackelberg Method for Robust Federated Learning. In Adversarial Machine Learning Frontiers Workshop at 40th International Conference on Machine Learning, 6 2023.
  74. Is Stochastic Mirror Descent Vulnerable to Adversarial Delay Attacks? A Traffic Assignment Resilience Study. 2023 62nd IEEE Conference on Decision and Control (CDC), 00:8328–8333, 2023.
  75. On the Resilience of Traffic Networks under Non-Equilibrium Learning. 2023 American Control Conference (ACC), 00:3484–3489, 2023.
  76. Modeling and analysis of leaky deception using signaling games with evidence. IEEE Transactions on Information Forensics and Security, 14(7):1871–1886, 2018.
  77. A game-theoretic taxonomy and survey of defensive deception for cybersecurity and privacy. ACM Computing Surveys (CSUR), 52(4):1–28, 2019.
  78. Zero-shot text-to-image generation. In M. Meila and T. Zhang, editors, Proceedings of the 38th International Conference on Machine Learning, volume 139 of Proceedings of Machine Learning Research, pages 8821–8831. PMLR, 18–24 Jul 2021.
  79. Cybert: Contextualized embeddings for the cybersecurity domain. In 2021 IEEE International Conference on Big Data (Big Data), pages 3334–3342, 2021.
  80. Physical intrusion games—optimizing surveillance by simulation and game theory. IEEE Access, 5:8394–8407, 2017.
  81. S. Rass and S. Schauer. Game theory for security and risk management. Springer International Publishing. doi, 10:978–3, 2018.
  82. Cryptographic games. Cyber-Security in Critical Infrastructures: A Game-Theoretic Approach, pages 223–247, 2020.
  83. B. Roberson. The colonel blotto game. Economic Theory, 29(1):1–24, 2006.
  84. Adversarial attacks on continuous authentication security: A dynamic game approach. In International Conference on Decision and Game Theory for Security, pages 439–458. Springer, 2019.
  85. Cyber-insurance framework for large scale interdependent networks. In Proceedings of the 3rd international conference on High confidence networked systems, pages 145–154, 2014.
  86. Flipit: The game of “stealthy takeover”. Journal of Cryptology, 26:655–713, 2013.
  87. Attention is All you Need. In Advances in Neural Information Processing Systems, volume 30 of NeuriPS. Curran Associates, Inc., 2017.
  88. Solution concepts in hypergames. Applied Mathematics and Computation, 34(3):147–171, 1989.
  89. Symbolic knowledge distillation: from general language models to commonsense models. In M. Carpuat, M.-C. de Marneffe, and I. V. Meza Ruiz, editors, Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pages 4602–4625, Seattle, United States, July 2022. Association for Computational Linguistics.
  90. Symbol-llm: Leverage language models for symbolic system in visual human activity reasoning. In A. Oh, T. Neumann, A. Globerson, K. Saenko, M. Hardt, and S. Levine, editors, Advances in Neural Information Processing Systems, volume 36, pages 29680–29691. Curran Associates, Inc., 2023.
  91. Z. Xu and Q. Zhu. A game-theoretic approach to secure control of communication-based train control systems under jamming attacks. In Proceedings of the 1st International Workshop on Safe Control of Connected and Autonomous Vehicles, pages 27–34, 2017.
  92. Designing Policies for Truth: Combating Misinformation with Transparency and Information Design. 2023 21st International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt), 00:127–134, 2023.
  93. R. Zhang and Q. Zhu. FlipIn: A game-theoretic cyber insurance framework for incentive-compatible cyber risk management of internet of things. IEEE Transactions on Information Forensics and Security, 15:2026–2041, 2019.
  94. R. Zhang and Q. Zhu. Optimal cyber-insurance contract design for dynamic risk management and mitigation. IEEE Transactions on Computational Social Systems, 9(4):1087–1100, 2021.
  95. A bi-level game approach to attack-aware cyber insurance of computer networks. IEEE Journal on Selected Areas in Communications, 35(3):779–794, 2017.
  96. T. Zhang and Q. Zhu. On the equilibrium elicitation of markov games through information design. arXiv preprint arXiv:2102.07152, 2021.
  97. T. Zhang and Q. Zhu. Forward-looking dynamic persuasion for pipeline stochastic bayesian game: A fixed-point alignment principle. arXiv preprint arXiv:2203.09725, 2022.
  98. T. Zhang and Q. Zhu. Stochastic game with interactive information acquisition: A fixed-point alignment principle. In 2023 59th Annual Allerton Conference on Communication, Control, and Computing (Allerton), pages 1–8. IEEE, 2023.
  99. Z. Zhang and Q. Zhu. Deceptive kernel function on observations of discrete pomdp. arXiv preprint arXiv:2008.05585, 2020.
  100. Q. Zhu and T. Başar. Dynamic policy-based ids configuration. In Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference, pages 8600–8605. IEEE, 2009.
  101. Deceptive routing games. In 2012 IEEE 51st IEEE Conference on Decision and Control (CDC), pages 2704–2711. IEEE, 2012.
  102. A game-theoretic approach to rule sharing mechanism in networked intrusion detection systems: Robustness, incentives and security. In 2011 50th IEEE Conference on Decision and Control and European Control Conference, pages 243–248. IEEE, 2011.
  103. Guidex: A game-theoretic incentive-based mechanism for intrusion detection networks. IEEE Journal on Selected Areas in Communications, 30(11):2220–2230, 2012.
  104. A stochastic game model for jamming in multi-channel cognitive radio systems. In 2010 IEEE International Conference on Communications, pages 1–6. IEEE, 2010.
  105. Q. Zhu and S. Rass. On multi-phase and multi-stage game-theoretic modeling of advanced persistent threats. IEEE Access, 6:13958–13971, 2018.
  106. Eavesdropping and jamming in next-generation wireless networks: A game-theoretic approach. In 2011-MILCOM 2011 Military Communications Conference, pages 119–124. IEEE, 2011.
  107. Network security configurations: A nonzero-sum stochastic game approach. In Proceedings of the 2010 American control conference, pages 1059–1064. IEEE, 2010.
  108. Q. Zhu and Z. Xu. Cross-layer design for secure and resilient cyber-physical systems. Springer, 2020.
  109. Interference aware routing game for cognitive radio multi-hop networks. IEEE Journal on Selected Areas in Communications, 30(10):2006–2015, 2012.
  110. Rt-2: Vision-language-action models transfer web knowledge to robotic control. In J. Tan, M. Toussaint, and K. Darvish, editors, Proceedings of The 7th Conference on Robot Learning, volume 229 of Proceedings of Machine Learning Research, pages 2165–2183. PMLR, 06–09 Nov 2023.
Citations (3)
View on Semantic Scholar

Summary

We haven't generated a summary for this paper yet.

Ai Sparkles Streamline Icon: https://streamlinehq.com Summarize Now