| NSF Org: |
CNS Division Of Computer and Network Systems |
| Recipient: |
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| Initial Amendment Date: | December 2, 2016 |
| Latest Amendment Date: | December 2, 2016 |
| Award Number: | 1714826 |
| Award Instrument: | Standard Grant |
| Program Manager: |
David Corman
CNS Division Of Computer and Network Systems CSE Directorate for Computer and Information Science and Engineering |
| Start Date: | September 1, 2016 |
| End Date: | August 31, 2019 (Estimated) |
| Total Intended Award Amount: | $118,776.00 |
| Total Awarded Amount to Date: | $118,776.00 |
| Funds Obligated to Date: |
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| History of Investigator: |
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| Recipient Sponsored Research Office: |
701 S NEDDERMAN DR ARLINGTON TX US 76019-9800 (817)272-2105 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
1 University of Texas at Arlington Arlington TX US 76019-0145 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): | CPS-Cyber-Physical Systems |
| Primary Program Source: |
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| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.070 |
ABSTRACT
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 PRODUCED AS A RESULT OF THIS RESEARCH
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PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
The goals of this CPS project include the following: 1) building a tractable modeling paradigm that captures the hybrid, stochastic, and interweaved dynamics of management-coupled cyber- and physical- infrastructures (MCCPIs), 2) understanding and modeling various types of adversaries in MCCPIs, 3) developing analytical and control strategies to mitigate threat impacts, and 4) using strategic air traffic management as a case study to implement and assess the modeling and control solutions developed for the general MCCPIs.
The outcomes of this project are summarized in the following six aspects. First, we conducted a survey study on the various types of threats. Second, we developed autonomous methods to monitor and detect abnormalities for network dynamics governed by layered queuing network models. Third, we conducted studies to model and capture uncertain weather spread using both model- and data- driven approaches. Fourth, we exploited the uncertainty-driven framework to quickly evaluate high-dimensional environmental impact to traffic systems. Fifth, we developed formal adaptive control solutions for systems of high-dimensional uncertainties using the method that integrates Multivariate Probabilistic Collocation Method (M-PCM) and Orthogonal Fractional Factorial Design (OFFD). Sixth, we developed data driven solutions that integrates query and effective similarity search for traffic management under uncertain weather disruption.
The outcomes also include 20 publications, including those published at IEEE Transactions on Systems, Man, and Cybernetics, Mathematics and Computers in Simulation, IEEE Control Systems Letters, and AIAA Journal of Aerospace Information Systems. This project outcomes benefit the air traffic management application with a suite of modeling, analysis, and control tools that mitigate threat impact to air traffic systems. The project benefits broad CPS domain with solutions to mitigate threats. It also benefits other disciplines, such as information networks, power networks, and road traffic systems that are also subject to man-made and natural threats.
The PI's active outreach and dissemination activities involve those in professional societies, such as the AIAA Intelligent Systems Technical Committee to contribute to policies in the aerospace domain. The PI was invited by the British Embassy to participate in the workshop on UK-US Next-generation Air Traffic Control Systems Opportunities for Improved Research Collaborations. The PI participated in drafting the ?Recommendations for Intelligent Systems in Aerospace: An AIAA/ISTC Position Statement? which led to broad dissemination to aerospace community that involves industry, academia, and government agencies. The PI also gave various presentations to universities, industries, and government. In addition, the PI served in a range of editor and organizing roles for conferences and journals related to this project. With respect to broadening participation, the PI guided multiple women students in this project, and also participated in in the Girlengineering Summer Program with lectures to K-12 students.
Last Modified: 11/29/2019
Modified by: Yan Wan
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