The National Science Foundation Division of Computer and Network Systems awarded a $731,838 Project Grant to the University of Texas at Dallas to develop algorithms and techniques for learning the hidden structure of digital and analog circuits from side-channel measurements. This work aims to advance hardware security and integrity checking by allowing adaptive interaction with circuits to intelligently model arbitrary analog circuit side-channels and utilize non-linear solvers and...
This Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) provides $203,206 to the University of Kansas Center for Research Inc. over a 4-year period from September 2024 to August 2028. The grant funds the development of a new framework for securing hardware intellectual property (IP) against reverse engineering, theft, and piracy threats. The project uses a combination of reinforcement learning...
This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) award of $206,439 to the University of Florida provides funding for the development of a scalable, learning-guided hardware IP protection platform. The key products and services being delivered under this 4-year grant include: Utilizing reinforcement learning techniques to discover novel attack vectors against logic locking and identify root causes behind...
This $500,000 National Science Foundation project grant supports research at the University of California, Riverside to develop novel machine learning-based electromigration analysis and optimization methods for very large-scale integrated circuit design. Specifically, the university will explore enhanced physics-informed neural network approaches for multi-segment interconnect stress analysis and full-chip electromigration-induced voltage drop modeling. Researchers will also develop efficient...
The University of California, Davis received a $111,647 project grant award from the National Science Foundation Division of Computer and Network Systems under the Computer and Information Science and Engineering federal grant program (CFDA 47.070). The award will support the development of CLOAK, a compilable architecture for secure IoT device production, testing, activation and operation. CLOAK aims to deliver circuit locking, obfuscation and authentication capabilities to strengthen...
This $174,705 project grant from the National Science Foundation's Computer and Information Science and Engineering program (CFDA 47.070) supports research at the Rochester Institute of Technology to develop a design space modeling framework for logic obfuscation configuration in integrated circuits. The goal is to automate identification of effective allocations of obfuscation resources that maximize system-wide security with minimal design overhead. Key products include quantifiable security...
This Project Grant from the National Science Foundation's Division of Computer and Network Systems, under the Computer and Information Science and Engineering program (CFDA 47.070), provides $173,000 to the Long Beach Research Foundation of California State University to investigate secure embedded field-programmable gate array (EFPGA) redaction solutions and dynamic key schemes for hardware security and reliability from March 2023 to February 2025. The project aims to develop a comprehensive...
This Project Grant award from the National Science Foundation's (NSF) Engineering program (CFDA 47.041) provides $199,437 to the University of Rhode Island (URI) to advance research in hardware security through the use of graph neural networks. The project aims to establish an infrastructure that leverages graph neural networks to investigate characteristics of different logic locking techniques, with the goal of enhancing the feasibility of logic locking within integrated circuit design...
The National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) federal grant program (CFDA 47.070) awarded a $148,347 project grant to the University of Maine System (UMS) to develop a new framework for microelectronic security and trust. The key elements of the project are: Using reinforcement learning techniques to discover novel attack vectors against logic locking and identify root causes behind successful attacks. Leveraging explainable artificial intelligence...
This National Science Foundation Project Grant of $526,968 will fund the development of countermeasures against laser-assisted side-channel attacks on integrated circuits and electronic systems from 2022 to 2025. Under the Computer and Information Science and Engineering program (CFDA 47.070), researchers at Worcester Polytechnic Institute will investigate "Eradicator," a multi-layer suite of sensors, randomization techniques, and tamper response mechanisms to avert such attacks....