Project Grant 2531027
- The National Science Foundation (NSF) awarded a $311,529 Project Grant to Princeton University under the CISE: Core Programs from the Computer and Information Science and Engineering (CFDA 47.070) federal grant program. The project, titled "CAREER: ENCAPSULATING UNSAFE CODE IN LOW-LEVEL SYSTEMS", seeks to develop strategies and mechanisms to safely utilize legacy software libraries with unsafe programming languages by combining hardware-based and language-based techniques. This will...
- This Project Grant award from the National Science Foundation's Computer and Information Science and Engineering (CISE) program (CFDA 47.070) provides $600,000 to Florida State University (FSU) to develop a security-focused framework to protect collaborative scientific computing in Machine Learning as a Service (MLaaS) environments. The key products and services to be delivered include: Robust model protection techniques to hinder reverse engineering of machine learning models while preserving...
- This National Science Foundation (NSF) Computer and Information Science and Engineering (CFDA 47.070) Project Grant award of $600,000 to Yale University will leverage the Rust programming language to enhance the correctness and reliability of systems software, such as operating systems. The project aims to develop innovative techniques for intralingual resource representation, design patterns for verifiable operating system implementation, and a hybrid approach combining formal and informal...
- This Project Grant award, provided by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070), aims to improve the security and resilience of machine learning (ML) software. The $262,828 award, issued on March 15, 2025, will support the development of methods for detecting and correcting non-functional vulnerabilities in ML libraries, such as denial-of-service attacks and side-channel attacks. This research...
- This Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) will fund a $1,200,000 project to develop practical, systematic fuzzing tools that enhance the security of scientific software. The 3-year project, led by the University of Utah, aims to address vulnerabilities in complex, multi-language scientific software by introducing (1) performant cross-language instrumentation, (2) automated...
- This $566,953 project grant awarded by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070) aims to address critical challenges in fine-grained information flow control (IFC) within software systems. The research primarily focuses on developing a novel IFC system tailored to the Rust programming language, leveraging its unique features. Key objectives include designing a static IFC library to minimize programming model...
- This federal Project Grant award in the amount of $175,123.00, awarded by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program, aims to develop new isolation mechanisms for secure and performant code execution on cloud computing infrastructure. The primary goal is to create a framework called COLONY that can better isolate programs running on shared cloud platforms, reducing the risk of security vulnerabilities, data leaks, and...
- This $194,999 Project Grant award, funded by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070), supports research to enforce expressive security policies using trusted execution environments. The project aims to advance the state-of-the-art for building secure systems by automatically placing security-critical application components within secure enclaves, reducing the programming challenges. The work includes developing a...
- 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)...
- New York University received a $499,748 project grant award from the National Science Foundation Office of Advanced Cyberinfrastructure on July 15, 2021. The award is part of the Computer and Information Science and Engineering program (CFDA 47.070) and will fund research to develop techniques for tracing runtime anomalies in code execution. Specifically, the grant will support the development of tools and methods to track anomalies during program execution in order to identify vulnerabilities...
This federal Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program provides $600,000 to New York University (NYU) to develop GRISL (General-purpose Rigorous Isolation for Science Libraries), a novel technology that strengthens the robustness and security of scientific computing software libraries. The goal is to isolate and harden these libraries, which are often written in low-level languages prone to memory corruption and other issues, in order to improve the reliability of critical scientific workflows, AI/ML applications, and high-performance computing systems across domains like physics, biology, and climate science. The 3-year project, running from January 1, 2026 to December 31, 2028, will introduce a lightweight, user-space containment approach to enable researchers to use legacy libraries safely without modifying the code, while providing advanced runtime safety checks and inter-library protection. This will help ensure the functional correctness and integrity of scientific computing infrastructure.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $600.0k | 7/28/25 |