Project Grant 2425665

Award Date 1/1/24
Completion Date 9/30/24
Dollars Obligated $123K
Federal Grant Program
47.070
Assistance Type
Project Grant
Place of Performance
Albany, CA 94710, USA
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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...
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This Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program, with a total funding of $122,767, supports a research project by the University of California, Berkeley aimed at hardening off-the-shelf software against side channel attacks.

The project consists of three main tasks: (1) reverse engineering hardware structures to determine potential attack vectors, (2) designing software transformations to protect against side channel leakage, and (3) developing automated tools to detect side channel vulnerabilities. The goal is to secure existing software deployed on hardware susceptible to side channel attacks, like those exploited by the Spectre and Meltdown vulnerabilities, until more secure hardware becomes available. The project will make its data, simulators, and code publicly available to aid in designing safer hardware and mitigating side channel leakage in software.

Generated 12/31/24, 10:07 AM