Project Grant 2132294
Award Date
4/1/22
Completion Date
12/31/22
Dollars Obligated
$255K
Federal Agency
National Science Foundation
Awardee
Anomalee Inc. (FG47SQJG18Q7)
Federal Grant Program
47.084
Assistance Type
Project Grant
Place of Performance
State College, PA, USA
Similar Awards
This $175,000 two-year project grant from the National Science Foundation's Computer and Information Science and Engineering program will fund research at Old Dominion University Research Foundation to advance secure deep learning systems. The awardee will systematically study existing neural network backdoor attacks to understand fundamental attack principles. Based on these findings, the research team will develop algorithms to accurately detect neural backdoors embedded in deep learning...
This $207,962 National Science Foundation (NSF) Computer and Information Science and Engineering (CFDA 47.070) grant awarded to Tufts University on February 1, 2024 will support research to enhance the robustness of artificial intelligence (AI) systems against hardware-oriented vulnerabilities. The project has four main thrusts: Designing algorithm-hardware collaborative backdoor attacks to exploit new adversarial vulnerabilities in deep neural networks. Developing methodologies to incorporate...
This Project Grant award, issued by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program, supports research to understand and mitigate deterministic model bit flip attacks on deep neural networks (DNNs). The $205,591 award to Arizona State University (ASU) aims to systematically investigate the vulnerability of quantized DNNs to hardware-based fault attacks that can manipulate model parameters, and develop algorithmic, system, and...
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)...
This Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) provides $174,998 to The Trustees of the Stevens Institute of Technology to investigate timing side channels in adaptive neural networks. The project aims to: (1) define a threat model for exploiting timing channels to gain sensitive user information, (2) develop a machine learning-based pipeline to utilize these timing channels, (3) create an...
This Project Grant award for $180,000.00, provided by the National Science Foundation (NSF) under the Mathematical and Physical Sciences federal grant program (CFDA 47.049), aims to advance the mathematical understanding of trustworthy artificial intelligence (AI) algorithms for threat detection. The primary objectives are to investigate few-shot learning techniques, which can build effective models from a very limited number of data samples, and to explore few-shot graph generation methods,...
This $349,828 Project Grant was awarded by the National Science Foundation (NSF)'s Computer and Information Science and Engineering (CISE) program (CFDA 47.070) to The Trustees of the University of Pennsylvania. The grant will fund research aimed at developing techniques to ensure trustworthiness and reliability of artificial intelligence (AI) systems that incorporate deep neural networks (DNNs), particularly those used in safety-critical applications. The key objectives are to: Design...
This Project Grant award, provided by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program, supports the development of Algorithm-Informed Neural Networks (AINNs), a novel approach to enhancing the transparency, reliability, and efficiency of artificial intelligence (AI) systems. The $150,000 award, made effective May 1, 2025 with an ultimate completion date of April 30, 2027, will enable researchers at the University of North...
This Project Grant from the National Science Foundation's Division of Computing and Communication Foundations, under the Computer and Information Science and Engineering federal grant program (CFDA 47.070), provides $199,999 to support the development of novel algorithms and schemes for ensuring robust operations of deep neural networks. The award to Texas A&M Engineering Experiment Station, doing business as Tees, will fund the Guardiann project from March 1, 2023 through February 28, 2026....
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...