Project Grant 2436155
- This Project Grant award, valued at $180,000.00 and provided by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070), supports research to evaluate the security landscape of machine learning (ML) and artificial intelligence (AI) technologies in electronic design automation (EDA) tools for the chip design industry. The key research aims include: (1) comprehensively examining the impact of input and training data perturbations and...
- 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...
- The National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program awarded a $600,000 project grant to the University of Delaware to develop a proactive and intelligent framework for securing system-on-chip (SoC) designs against power side-channel and fault injection attacks. The project aims to shift the research focus from reactive defense to built-in security assurance by integrating advanced cryptographic primitives and game-theoretic methods into the SoC...
- The National Science Foundation (NSF) awarded a $402,229 Computer and Information Science and Engineering (CISE) Program grant to The Research Foundation For The State University Of New York, doing business as Stony Brook University. This 1-year grant, effective November 1, 2023, supports research and development focused on improving the security of machine learning (ML) systems that leverage third-party, pre-trained models. The project aims to develop rigorous methods for detecting and...
- The National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program awarded a $500,000 Project Grant to the Regents of the University of California at Riverside (CFDA 47.070) effective June 15, 2025, with a completion date of May 31, 2028. The grant supports research to understand and mitigate security vulnerabilities in machine learning models that may arise from exploiting unused model parameters. The project aims to empirically study the...
- The National Science Foundation (NSF) awarded a $600,000 Project Grant under the Computer and Information Science and Engineering (CISE) program to New York University (NYU) to investigate the risks of AI-generated code in the software supply chain. The 3-year project, which began on June 1, 2024, aims to: (i) develop techniques to distinguish human-written code from AI-generated code, (ii) measure the prevalence and security implications of AI-generated code in open-source software, and (iii)...
- The National Science Foundation (NSF) is providing a $206,382 Project Grant under its Computer and Information Science and Engineering (CISE) program to the Illinois Institute of Technology (IIT) Sponsored Research and Programs Division. The objective of this 5-year award is to design a trustworthy, flexible, and generalizable machine learning framework that can provide robustness against common privacy and security attacks. The project will develop novel information-theoretic representation...
- This $250,000 Project Grant from the National Science Foundation's Computer and Information Science and Engineering program will fund research at Northeastern University to improve the security of machine learning models in multi-tenant cloud field programmable gate array (FPGA) environments. The three-year award aims to advance understanding of vulnerabilities in cloud-FPGAs shared by multiple tenants, where a malicious actor could potentially manipulate another tenant's machine learning...
- This $300,000 National Science Foundation project grant supports research into robust machine learning under sparse adversarial attacks through 2025. Funded under the Computer and Information Science and Engineering program (CFDA 47.070), the University of California, Santa Barbara will develop theoretical frameworks and defense methods to make machine learning models resilient against perturbations affecting few data points. Specifically, the researchers aim to establish fundamental limits of...
- The National Science Foundation (NSF) awarded a $431,250 Project Grant under the Computer and Information Science and Engineering (CFDA 47.070) program to Carnegie Mellon University (CMU) to develop principled defenses against vulnerabilities in modern machine learning (ML) systems. The goal is to make robustness a core design property rather than an afterthought, bridging rigorous analysis with practical experimentation. The project will proceed along three technical thrusts: 1) robust...
The National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program awarded a $420,000 Project Grant to New York University (NYU) for the project "Collaborative Research: SATC: CORE: SMALL: Evaluating the Security Landscape of Machine Learning Enabled Electronic Design Automation". The 3-year project, starting on October 1, 2025, will comprehensively examine the impact of input and training data perturbations and attacks on the quality, performance, and security of AI/ML-based electronic design automation (EDA) tools used in the chip design industry. The research aims to enable the trustworthy adoption of AI/ML methods in chip design, enhancing productivity and quality while ensuring security. The project pursues these goals through three research thrusts investigating perturbation-based attacks, backdoor attacks, and defense mechanisms against such threats to ML-enabled EDA tools.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $420.0k | 8/7/25 |