Project Grant 2431547
Award Date
1/1/25
Completion Date
12/31/27
Dollars Obligated
$238K
Federal Agency
Division of Computer and Network Systems
Federal Grant Program
47.070
Assistance Type
Project Grant
Place of Performance
Hoboken, NJ 07030, USA
Similar Awards
This $362,141 federal Project Grant award, provided by the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070), supports a three-year collaborative research project between York College and Stevens Institute of Technology to explore cybersecurity and privacy enhancement techniques for Artificial Internet of Things (AIoT) systems. The key research tasks include: 1) building a joint AIoT research testbed, 2) investigating data poisoning...
This $381,264 project grant from the National Science Foundation's Computer and Information Science and Engineering program (CFDA 47.070) supports research at the University of Florida to develop hardware-efficient artificial intelligence techniques for federated learning across diverse Internet of Things devices. Over a three-year period ending September 2025, the research team will work to enable quantization and pruning of neural networks in a way that accounts for the varied computational...
This $299,898 Project Grant from the National Science Foundation's Computer and Information Science and Engineering program will fund research at New York University to develop privacy-preserving machine learning models for Internet of Things device analytics and behavior prediction. The three-year award beginning October 1, 2022 aims to address privacy and network resource challenges posed by growing IoT adoption in homes. Specifically, the university will create an automated infrastructure...
This $375,022 federal Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) will support research to develop new cross-layer computing architectures and processing techniques for resource-constrained Internet of Things (IoT) devices. The project aims to transition IoT computing from a cloud-centric to a data-centric paradigm, enabling autonomous edge processing and decision-making to reduce data...
This $300,004 National Science Foundation project grant supports the development of privacy-preserving Internet of Things analytics and behavior prediction methodologies at North Carolina State University from October 2022 through September 2025. Funded under the NSF's Computer and Information Science and Engineering program (CFDA #47.070), the research aims to address challenges related to resource utilization, security, and privacy posed by growing IoT adoption in home networks. The project...
This $600,000 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) aims to advance the security and privacy of on-device machine learning (ML) models used in Internet of Things (IoT)-driven scientific cyberinfrastructure (CI). The project has two primary goals: 1) Developing a novel runtime detection and prevention mechanism to protect ML models from extraction attacks, utilizing techniques like multi-level...
This $151,946 federal Project Grant award from the National Science Foundation's Computer and Information Science and Engineering (CFDA 47.070) program is supporting the "DANGER-IOT" research project led by Northeastern University. The project aims to develop advanced machine learning models for detecting malware across heterogeneous Internet-of-Things (IoT) platforms. The key goals are to create a generic malware detection model that works across diverse IoT systems, ensure efficiency...
This Project Grant award of $145,830.00 from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) will support research at Old Dominion University Research Foundation (Odurf) to develop a secure and fully decentralized machine learning framework for heterogeneous Internet of Things (IoT) networks. The key objectives are to design a decentralized learning system that can effectively learn patterns from diverse, distributed IoT...
This three-year, $244,997 Project Grant from the National Science Foundation's Computer and Information Science and Engineering program aims to develop scalable methods for analyzing large-scale network traffic data to quantify internet-of-things (IoT) device insecurities and characterize malicious IoT campaigns. The awardee, San Diego State University Research Foundation, will work with collaborators to design algorithms and formal methods using supervised deep learning to fingerprint exploited...
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...