Overview
The Confidential Computing Consortium (CCC) call for research proposals on Confidential Computing is now closed. We are no longer accepting new applications for this funding cycle. Thank you to everyone who submitted a proposal, we received strong interest across our three areas of primary interest:
- Addressing emerging challenges in scaling confidential computing
- Novel applications and case studies in privacy domain like data protection, data sharing, data sovereignty and verifiable transparency
- Security hardening, security review/analysis and verification of confidential computing components e.g., architectures, firmware, software, and protocols
Application Timeline (Closed)
- May 1, 2026: Applications Open
- June 1, 2026: Applications Close
- July 1, 2026: Recipients Announced
2026 Research Grant Recipients
- Leakage-Aware Security Analysis of KV Cache Management in Confidential GPU LLM Serving, David Oswald and Qifan Wang, Durham University – This project will investigate the security of KV cache management in confidential GPU LLM serving. The project will focus on the standard GPU TEE threat model: a malicious cloud host with hypervisor, observing side channels through software-visible timing of GPU operations, and power measurements from host-accessible BMC/IPMI readings to board-level power traces. The project will study whether such observations can reveal prompts, including prompt length, prefix-cache hits and misses, request boundaries, or membership in a known candidate prompt set.
- Deko: A Hardware-software Co-Design for Runtime Attestation of Privacy Policy Enforcement, Chenghong Wang, Indiana University – This project proposes to develop Deko, to support end-to-end verifiable data provenance using Confidential Virtual Machines (CVMs). Deko allows data owners and downstream users to verify the methodological lineage of a derived dataset: what inputs were used, which components processed them, which information-flow policies were enforced, and which intermediate artifacts contributed to the final output. This capability addresses a fundamental gap in today’s confidential-computing and TEE based privacy-preserving data curation and sharing systems: While TEEs protect data in use, they do not by themselves prove that a dataset was processed according to a specified governance policy.
Requirements
Proposals should include:
- A summary of the project (2 pages maximum) explaining the area of focus, a description of techniques, any relevant prior work, and a timeline with milestones and expected outcomes.
- A draft budget description (1 page) including a cost of the requested award and an explanation of how funds would be spent.
- Curriculum Vitae for all project participants.
- Organization details including tax information and administrative contact details.
Eligibility
- Awards must comply with applicable U.S. and international laws, regulations and policies.
- Applicants must be current full-time faculty at an accredited academic institution that awards research degrees to PhD students or at a reputed research institute.
- Applicants must be the Principal Investigator on any resulting award.
Selection Criteria
The program committee will make the grant decision based on the proposal quality and potential impacts to the research and open source community.
Expected Outcomes
An emphasis should be placed on open collaboration and community benefit. Therefore, we expect successful proposals to produce outcomes that contribute to the broader Confidential Computing ecosystem. This includes, but is not limited to, the publication of research findings in a public forum, the release of open source code under a permissive license, and the contribution of new features or improvements to existing open-source projects within the Confidential Computing Consortium. Awardees will be encouraged to present their work at relevant industry conferences and to engage with the community to ensure their research has a lasting and positive impact. If needed, members of the Confidential Computing Consortium Technical Advisory Council can offer mentorship, consultation and advice on the research.
Additional Information
Payment will be made to the proposer’s host university as an unrestricted gift. Because of its nature, salary/headcount could be included as part of the budget presented for the RFP. Since the award/gift is paid to the university, they will be able to allocate the funds to that winning project and have the freedom to use as they need. Award funds can be used to cover a researcher’s salary. Typically research funds ideally cover graduate or post-graduate students’ employment/tuition and other research costs (e.g., equipment, laptops, incidental costs).
Terms & Conditions
By submitting a proposal, you are authorizing the Confidential Computing Consortium to evaluate the proposal for a potential award, and you agree to the terms herein.
- You agree that the Confidential Computing Consortium will not be required to treat any part of the proposal as confidential or protected by copyright.
- You agree and acknowledge that personal data submitted with the proposal, including name, mailing address, phone number, and email address of you and other named researchers in the proposal may be collected, processed, stored and otherwise used by the Confidential Computing Consortium for the purposes of evaluating the contents of the proposal.
- You acknowledge that neither party is obligated to enter into any business transaction as a result of the proposal submission, the Confidential Computing Consortium is under no obligation to review or consider the proposal, and neither party acquires any intellectual property rights as a result of submitting the proposal.
Program Committee
- Mingshen Sun, TikTok (Chair)
- Fritz Alder, Nvidia
- Mike Bursell, Confidential Computing Consortium
- Caroline Perez-Vargas, Microsoft
- Yu Ding, Google
- Kevin Hui, Meta