Project Grant 2443671
- This two-year National Science Foundation project grant of $137,683 aims to enhance the reliability and privacy of graphics processing unit (GPU)-based deep learning computing. Funded under the Computer and Information Science and Engineering program, the award supports research at West Virginia University to address vulnerabilities in GPU architecture and design lightweight protection schemes. Specifically, the university researchers will explore vulnerabilities impacting GPU-based deep...
- The University of Rochester was awarded a $599,943 Project Grant by the National Science Foundation's (NSF) Integrative Activities program (CFDA 47.083) to enhance the security of GPU computing for AI-driven scientific workflows. The project, titled "SECURING GPU COMPUTING FOR AI-DRIVEN SCIENTIFIC WORKFLOWS - ENHANCING MEMORY SAFETY IN GRAPHICS PROCESSING UNITS (GPUS)", aims to address the urgent need to strengthen GPU software security against memory safety risks. The project...
- 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 $247,059 project grant awarded by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) Program (CFDA 47.070) supports research to secure cloud-based Field Programmable Gate Arrays (FPGAs) from analog side-channel attacks. The project, led by the University of California, Santa Cruz (UCSC), will study and characterize "FPGA pentimenti" - data leakage between subsequent FPGA users through analog effects. The research aims to establish the...
- This $600,000 Project Grant from the National Science Foundation's Computer and Information Science and Engineering program (CFDA 47.070) supports research at the University of California, Davis to address security vulnerabilities in cloud computing infrastructure and develop defenses against targeted microarchitectural attacks. Over a four-year period from July 2022 to June 2026, the university will conduct a comprehensive threat analysis of cloud schedulers and investigate software-based and...
- The National Science Foundation (NSF) awarded a $299,995 Project Grant under the Computer and Information Science and Engineering (CFDA 47.070) program to the University of Massachusetts (UMass) to develop novel security approaches for protecting field-programmable gate arrays (FPGAs) used in cloud computing environments. The key objectives of this 3-year project are to introduce secure operating mechanisms and a security and queue management unit (SQMU) to enable controlled sharing of FPGAs...
- This National Science Foundation (NSF) Computer and Information Science and Engineering (CFDA 47.070) Project Grant, awarded to the University of California, San Diego (UCSD) on December 1, 2024, provides $225,934 to study and develop mitigations for "FPGA pentimenti" - data leakage between subsequent users of time-shared cloud-based field programmable gate arrays (FPGAs) through analog side channels. The project aims to characterize the bounds of data recovery capabilities within...
- This two-year, $600,000 Project Grant from the National Science Foundation's Computer and Information Science and Engineering program aims to advance side-channel analysis and protection through deep learning techniques. Funded research at Northeastern University will develop novel methods for applying deep neural networks to both microarchitectural side-channel attacks and effective countermeasures. Key products include a persistent cache monitoring mechanism to improve observation of victim...
- This Project Grant award of $246,516 from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program supports research to enhance the security and robustness of machine learning (ML) systems in multi-tenant cloud FPGA (field programmable gate array) environments. The project aims to: (1) understand the vulnerabilities of ML cloud-FPGA systems and explore defensive approaches; (2) advance the security of ML cloud systems against hardware-based model...
- This federal Project Grant award from the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CISE, CFDA 47.070) program supports research to address vulnerabilities in the physical security of hardware systems related to side-channel attacks. The $510,336 award to Worcester Polytechnic Institute (WPI), provided from July 1, 2025 to June 30, 2028, aims to develop advanced physical probing models, scalable validation tools, and provably secure design...
This $450,030 Project Grant awarded by the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program will support research at Clemson University to investigate and mitigate information leakage threats in real-world GPU-as-a-Service (GPUaaS) environments. The project aims to uncover practical side-channel attacks that exploit GPU microarchitectural components to expose sensitive information from virtual desktop users and extract proprietary neural network designs during inference. Systematic measurement studies will also be conducted to understand GPU resource management and co-residency patterns in public cloud deployments. Additionally, the project will develop effective and practical countermeasures against these information leakage threats. This research is expected to lead to stronger data privacy guarantees for cloud users and provide actionable security guidance for the rapidly growing GPUaaS market.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $450.0k | 7/16/25 |