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U.S. National Science Foundation

Cybersecurity Innovation for Cyberinfrastructure (CICI)

The objective of the Cybersecurity Innovation for Cyberinfrastructure (CICI) program is to advance scientific discovery and innovation by enhancing the security and privacy of cyberinfrastructure. CICI supports efforts to develop, deploy and integrate cybersecurity that will benefit the broader scientific community by securing science data, computation, collaborations workflows, and infrastructure. CICI recognizes the unique nature of modern, complex, data-driven, distributed, rapid, and collaborative science and the breadth of infrastructure and requirements across scientific disciplines, practitioners, researchers, and projects. CICI seeks proposals in four program areas: 1.  Usable and Collaborative Security for Science (UCSS): Projects in this program area should support novel and/or applied security and usability research that facilitates scientific collaboration, encourages the adoption of security into the scientific workflow, and helps create a holistic, integrated security environment that spans the entire scientific cyberinfrastructure ecosystem. 2.  Reference Scientific Security Datasets (RSSD): Projects in this program area should leverage instrumented cyberinfrastructure to capture metadata from scientific workflows and workloads as reference data artifacts that can help support reproducible security research, testing and evaluation. 3.  Transition to Cyberinfrastructure Resilience (TCR): Projects in this program area should improve the robustness, trustworthiness, integrity, and/or resilience of scientific cyberinfrastructure through testing, evaluation, hardening, validation, and technology transition of novel cybersecurity research. The TCR area further encourages transition activities that advance the deployment and use of reproducibility in CI, workflows, and data. 4.  Integrity, Provenance, and Authenticity for Artificial Intelligence Ready Data (IPAAI): Projects in this program area should enhance confidence and reproducibility in AI produced scientific results by improving the integrity, provenance, and authenticity of scientific datasets used by Artificial Intelligence systems.

Eligibility

*Who May Submit Proposals: Proposals may only be submitted by the following: -Non-profit, non-academic organizations: Independent museums, observatories, research laboratories, professional societies and similar organizations located in the U.S. that are directly associated with educational or research activities. -Institutions of Higher Education (IHEs): Two- and four-year IHEs (including community colleges) accredited in, and having a campus located in the US, acting on behalf of their faculty members. Special Instructions for International Branch Campuses of US IHEs: If the proposal includes funding to be provided to an international branch campus of a US institution of higher education (including through use of sub-awards and consultant arrangements), the proposer must explain the benefit(s) to the project of performance at the international branch campus, and justify why the project activities cannot be performed at the US campus.

  • Others (see text field entitled "Additional Information on Eligibility" for clarification)

Application requirements

  • 1Apply through Grants.gov (SAM.gov registration required).

How to apply

Apply online at https://www.grants.gov/search-results-detail/358004 via Grants.gov. Agency contact: U.S. National Science Foundation — [email protected].

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