This $910,624 Project Grant award from the National Science Foundation's (NSF) Integrative Activities program (CFDA 47.083) to Trustees of Boston University aims to accelerate the development of trusted, low-overhead tools that enable computation directly on encrypted data. The project will explore a novel paradigm for circuit obfuscation and establish the security and efficiency of a recently proposed scheme for computation on encrypted data, referred to as Encrypted Operator Computing (EOC)....
The National Science Foundation awarded a $174,855 Project Grant to Michigan Technological University under the Computer and Information Science and Engineering program (CFDA 47.070). The grant supports development of techniques to enable secure machine learning queries over encrypted databases in cloud computing. Specifically, the university will develop an index-aided approach employing encryption of individual data items and generation of secure index items to simultaneously achieve strong...
This Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) totaling $189,898 aims to accelerate the development of efficient, scalable, and practical privacy-preserving machine learning solutions. The key products and services to be delivered under this 3-year award, which begins on October 1, 2024, include: Orchestrating information representation and model sparsity in the encryption domain to...
This Project Grant award from the National Science Foundation (NSF) under the Computer and Information Science and Engineering program (CFDA 47.070) is focused on accelerating privacy-preserving machine learning as a service. The key objectives are to: (1) orchestrate information representation and model sparsity in the encryption domain to reduce memory and computation footprint; (2) overcome high overhead associated with multi-party computation (MPC)-based solutions through techniques like...
This $174,810 federal Project Grant award from the National Science Foundation's Computer and Information Science and Engineering (CFDA 47.070) program supports research at Northern Arizona University (NAU) to optimize resource-intensive operations in existing fully homomorphic encryption schemes and integrate the optimized algorithm into federated learning frameworks. The project aims to enhance security in Internet of Things communications by enabling secure data analysis on encrypted data...
This Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) aims to address challenges in integrating confidential computing into scientific workflows. The $432,485 award to the University of Maryland Baltimore County (UMBC) will fund research to develop a scientist-friendly framework for trusted execution environment (TEE)-based confidential computing and a holistic approach to studying security and privacy...
The National Science Foundation (NSF) awarded a $599,725 Project Grant under the Computer and Information Science and Engineering (CFDA 47.070) federal grant program to The University of Central Florida (UCF) to develop a system for verifiable fully homomorphic encryption (FHE). The project aims to create a solution that ensures both confidentiality and integrity of computations performed on encrypted data, enabling safer and broader applications of privacy-preserving technologies in sensitive...
The National Science Foundation awarded a $600,000 Project Grant to the Trustees of Boston University under the Computer and Information Science and Engineering federal grant program (CFDA 47.070). The three-year award will support research into developing new differentially private stochastic optimization algorithms for training neural networks while preserving individual privacy. Specifically, the grantee will investigate fundamental tradeoffs between privacy and performance in modern...
This $240,062 project grant, awarded by the National Science Foundation (NSF) through its Computer and Information Science and Engineering (CISE) Program (CFDA 47.070), aims to develop efficient and scalable hardware architectures for privacy-preserving neural network inference based on ciphertext-ciphertext fully homomorphic encryption (FHE). The research will focus on designing optimized hardware building blocks, such as polynomial multipliers, and a reconfigurable FHE architecture that...
This $193,399 federal Project Grant award, provided by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program, supports research to strengthen the foundations of computational intractability needed for robust cryptography. The project aims to explore novel resource-constrained adversarial models to improve cryptographic security, with two concrete goals: (1) improved cryptographic hardness amplification, yielding extremely hard...
This $209,368 federal Project Grant award from the National Science Foundation's Integrative Activities program (CFDA 47.083) aims to develop trusted, low-overhead tools that enable computation directly on encrypted data. The goal is to accelerate the creation of new capabilities that allow confidential data to be shared with untrusted parties who can extract insights without accessing the unencrypted data. This would increase public trust in modern AI tools and enable data-powered, socially responsible innovation. The award brings together expertise from physics, mathematics, and computer science to explore a novel paradigm for circuit obfuscation and establish the security and efficiency of a recently proposed encrypted operator computing scheme. The project seeks to leverage physics-inspired approaches to create practical cryptographic tools that address significant security and privacy concerns in an AI-powered economy.