This $147,212 federal Project Grant awarded by the National Science Foundation's Engineering program (CFDA 47.041) supports research to enable the development of a framework for safe control in autonomous systems in the presence of sensor and actuator faults and cyber attacks. The research combines techniques from control theory, machine learning, and system security to provide provable safety guarantees across a range of autonomous systems and fault/attack scenarios. Key focus areas include...
The National Science Foundation awarded a $324,687 Project Grant to the University of California, Davis under the Engineering federal grant program (CFDA 47.041) for the period of June 1, 2022 through May 31, 2025. The grant funds research to develop active control-enabled approaches for detecting cyberattacks on process control systems used in chemical manufacturing. Key activities include formulating optimization problems to ensure cyberattack detectability during process control system...
This Project Grant award, provided by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070), supports research to characterize the vulnerabilities of learning-based controllers in networked cyber-physical systems (CPS). The $149,985 award will enable the University of Alabama in Huntsville (UAH) to develop real-time reward manipulation schemes, multi-level attack strategies, and data-enabled detection methods to...
This National Science Foundation (NSF) Engineering (CFDA 47.041) grant award, titled "CAREER: DATA-ENABLED NEURAL MULTI-STEP PREDICTIVE CONTROL (DEMUSPC): A LEARNING-BASED PREDICTIVE AND ADAPTIVE CONTROL APPROACH FOR COMPLEX NONLINEAR SYSTEMS", provides $655,248 in funding to the University of Houston System from September 2024 through August 2029. The project aims to conduct fundamental research to develop data-driven and learning-based predictive and adaptive control approaches, with...
This $199,867 National Science Foundation project grant supports research at the University of Michigan to develop formal methodologies for synthesizing cyber-secure and resilient control logic for networked discrete-event systems subject to cyber attacks. Funded under the NSF Engineering program (CFDA 47.041), the three-year project commencing September 2022 aims to enhance the reliability of advanced control systems through model-based approaches. Researchers will extend diagnosability...
This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program Project Grant award of $299,897 to Lamar University aims to develop an interdisciplinary cybersecurity education program to support the workforce needs of critical energy and chemical infrastructure. The project will generate knowledge- and practice-oriented content for integration into chemical engineering, computer science, and criminal justice curriculums. Key activities include developing a...
This five-year, $492,055 project grant from the National Science Foundation's Office of Advanced Cyberinfrastructure, under the Computer and Information Science and Engineering program (CFDA 47.070), will fund research and education activities at the University of Texas at El Paso to enhance critical infrastructure resiliency. Specifically, the university will develop overhead-aware provenance frameworks to incorporate implicit resiliency and assure trustworthiness in operational technology...
This $300,027 Project Grant awarded by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program supports research to develop secure and trustworthy learning-based control systems for cyber-physical systems (CPS). The project aims to: a) Develop a real-time reward manipulation scheme for learning-based controllers b) Design multi-level attack schemes on reward signals in a distributed CPS control architecture c) Develop data-enabled strategies for...
This $255,973 National Science Foundation Project Grant will fund the development of cyber defense technologies for industrial control systems. Specifically, the awardee Blocmount Corporation will utilize machine learning, statistics, and control theory methods to build an extensible library of monitoring checks as well as an AI-based defense agent and cloud service. These products aim to provide early detection of cyberattacks targeting industrial control systems, addressing threats posed by...
This Project Grant award, valued at $600,000 and spanning from December 2024 to November 2027, is funded by the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070). The key objectives of this project are to: Develop a comprehensive framework for end-to-end verification of control systems, encompassing high-level hybrid models down to the verification of embedded C code. This includes designing an end-to-end process to...
This $108,510 federal Project Grant award from the National Science Foundation's Engineering program (CFDA 47.041) supports the development of a comprehensive solution to provide security and safety assurance for industrial control systems (ICS) against malicious cyber-attacks. The key products and services to be delivered include:
Developing an "operator-automation shared protection framework" that integrates human-on-the-loop explainable machine learning, detection, and recovery control to enable real-time decision-making while valuing human operator feedback. This aims to prevent over-trust in autonomy for safety-critical ICS.
Designing a real-time provably safe control system to restore ICS to normal operation without violating safety constraints, in the event of a detected cyber-attack.
Evaluating, demonstrating, and disseminating best practices of the proposed framework on simulated and real ICS testbeds to lower barriers to ICS security research and education, particularly for underrepresented student populations.
The award was granted to the University of Houston System, a Hispanic Serving Institution, and will run from November 2024 to May 2025. No sub-awards are planned under this grant.