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CPS: TTP Option: Synergy:

About the Project

CPS: TTP Option: Synergy: Collaborative Research: Threat-Assessment Tools for Management-Coupled Cyber- and Physical- Infrastructure
NSF Project Numbers and Links: 1714826, 1544863

Strategic decision-making for physical-world infrastructures is rapidly transitioning toward a pervasively cyber-enabled paradigm, in which human stakeholders and automation leverage the cyber-infrastructure at large (including on-line data sources, cloud computing, and handheld devices). This changing paradigm is leading to tight coupling of the cyber- infrastructure with multiple physical- world infrastructures, including air transportation and electric power systems. These management-coupled cyber- and physical- infrastructures (MCCPIs) are subject to complex threats from natural and sentient adversaries, which can enact complex propagative impacts across networked physical-, cyber-, and human elements.

We propose here to develop a modeling framework and tool suite for threat assessment for MCCPIs. The proposed modeling framework for MCCPIs has three aspects: 1) a tractable moment-linear modeling paradigm for the hybrid, stochastic, and multi-layer dynamics of MCCPIs; 2) models for sentient and natural adversaries, that capture their measurement and actuation capabilities in the cyber- and physical- worlds, intelligence, and trust-level; and 3) formal definitions for information security and vulnerability. The attendant tool suite will provide situational awareness of the propagative impacts of threats. Specifically, three functionalities termed Target, Feature, and Defend will be developed, which exploit topological characteristics of an MCCPI to evaluate and mitigate threat impacts. We will then pursue analyses that tie special infrastructure-network features to security/vulnerability. As a central case study, the framework and tools will be used for threat assessment and risk analysis of strategic air traffic management. Three canonical types of threats will be addressed: environmental-to-physical threats, cyber-physical co-threats, and human-in-the-loop threats. This case study will include development and deployment of software decision aids for managing man-made disturbances to the air traffic system.

Publications

  • C. He, Y. Wan, and F. Lewis, “On the Identifiability of the Influence Model for Stochastic Spatiotemporal Spread Processes,” IEEE Transactions on Systems, Man, and Cybernetics, accepted, April 2019.
  • J. Xie, Y. Wan, Y. Zhou, K. Mills, J. J. Filliben, and Y. Lei, “Effective Uncertainty Evaluation in Large-Scale Systems (book chapter),” Principles of Cyber-Physical Systems, Cambridge University Press, accepted for publication, pp. 1-25, 2019.
  • M. Liu, Y. Wan, Z. Lin, F. L. Lewis, J. Xie, and B. A. Jalaian, “Computational Intelligence in Uncertainty Quantification for Learning Control and Differential Games,” accepted, Book Chapter, 2019.
  • C. He, Y. Wan, Y. Gu, and F. Lewis, “Reinforcement Learning-based Approximate Minimum Time Path Planning of UAVs in Wind Fields,” submitted to American Control Conference, 2019.
  • C. He, Y. Wan, Y. Gu, and J. Xie, “Spatiotemporal Scenario Data-Driven Decision For the Path Planning of Multiple UASs,” to be submitted to AIAA Journal of Aerospace Information Systems.
  • C. He and Y. Wan, “Clustering Stochastic Weather Scenarios using Influence Model-based Distance Measures,” in Proceedings of AIAA Aviation Conference, Dallas, TX, June 17-21, 2019.
  • J. Xie, A. R. Kothapally, Y. Wan, C. He, C. Taylor, C. Wanke, and M. Steiner, “Similarity Search of Spatiotemporal Scenario Data for Strategic Air Traffic Management,” AIAA Journal of Aerospace Information Systems, vol. 16, no. 5, pp. 187-202, May 2019.
  • J. Xie, Y. Wan, K. Mills, J. J. Filliben, Y. Lei, and Z. Lin, “M-PCM-OFFD: An Effective Output Statistics Estimation Method for Systems of High Dimensional Uncertainties Subject to Low-Order Parameter Interactions,” Mathematics and Computers in Simulation, vol. 159, pp. 93-118, May 2019.
  • C. He, Y. Wan, and F. Lewis, “On the Identifiability of the Influence Model for Stochastic Spatiotemporal Spread Processes,” in Proceedings of American Control Conference, Philadelphia, PA, July 10-12, 2019.
  • A. Kothapally, J. Xie, H. Nguyen, and Y. Wan, “Similarity search of spatiotemporal scenarios for strategic air traffic management,” in Proceedings of the AIAA Aviation Conference, June 2018.
  • J. Xie, Y. Wan, K. Mills, J. J. Filliben, and F. L. Lewis, “A Scalable Sampling Method to High-Dimensional Uncertainties for Optimal and Reinforcement Learning-Based Controls,” IEEE Control Systems Letters, vol. 1, no. 1, pp. 98–103, July 2017.
  • J. Torres, S. Roy, and Y. Wan, “Sparse resource allocation for linear network spread dynamics,” IEEE Transactions on Automatic Control, vol. 62, no. 4, pp. 1714–1728, 2017.
  • M. Xue, S. Roy, C. Taylor, S. Zobell, C. Wanke, and Y. Wan, “A stochastic weather-impact simulator for strategic air traffic management,” Journal of Aerospace Operations, no. 1-2, pp. 25–45, 2017.
  • J. Xie and Y. Wan, “A Network Condition-Centric Flow Selection and Rerouting Strategy to Mitigate Air Traffic Congestion under Uncertainties,” in 17th AIAA Aviation Technology, Integration, and Operations Conference. Reston, Virginia: American Institute of Aeronautics and Astronautics, June 2017.
  • J. Xie, C. He, Y. Wan, K. Mills, and C. Dabrowski, “A Layered and Aggregated Queuing Network Simulator for Detection of Abnormalities,” in Winter simulation Conference, Las Vegas, NV, December 2017.
  • J. Xie, Y. Wan, and F. Lewis, “Strategic Air Traffic Management under Uncertainties using Scalable Sampling-based dynamic Programming and Q-learning Approaches,” in Proceedings of Asian Control Conference, Australia, December 2017.
  • Y. Gu, Y. Wan, and C. Tschan, in Recommendations for Intelligent Systems in Aerospace: An AIAA/ISTC Position Statement. AIAA ISTC, 2017.
  • Y. Wan, R. Kicinger, and K. Subbarao, “Air Traffic Management,” in AIAA Roadmap for Intelligent Sysems in Aerospace. AIAA, 2016.
  • J. Xie, Y. Wan, Y. Zhou, S.-L. Tien, E. Vargo, C. Taylor, and C. Wanke, “Distance measure to cluster spatiotemporal scenarios for strategic air traffic management,” Journal of Aerospace Information Systems, vol. 12, no. 8, pp. 543–563, 2015.
  • J. Torres, S. Roy, and Y. Wan, “Sparse allocation of resources in dynamical networks with application to spread control,” in Proceedings of the American Control Conference, vol. 2015-July, 2015.
  • S. Roy, Y. Wan, and J. Xie, “Proactive and reactive management of nonweather capacity disruption events in the national airspace system: A flow modeling and design approach,” in 15th AIAA Aviation Technology, Integration, and Operations Conference, 2015.
  • J. Xie and Y. Wan, “Scalable Multidimensional Uncertainty Evaluation Approach to Strategic Air Traffic Flow Management,” in AIAA Modeling and Simulation Technologies Conference. Reston, Virginia: American Institute of Aeronautics and Astronautics, June 2015.
  • N. Ekedebe, W. Yu, and Y. Wan, “Securing Transportation Cyber-Physical Systems,” in Securing Cyber-Physical Systems. CRC Press, October 2015, pp. 163–196.
  • J. Xie, Y. Zhou, K. Mills, J. J. Filliben, and Y. Lei, “Effective Uncertainty Evaluation in Large-Scale Systems (book chapter),” in Principles of Cyber-Physical Systems. Springer, 2017.