Standardizing Data and Metadata from Wearable Devices (R01 Clinical Trial Not Allowed)

Measurement Science and Engineering (MSE) Research Grant Programs (ITL Grant Program) is sponsored by National Institute of Standards and Technology (NIST). The ITL Grant Program provides financial assistance to support research consistent with the ITL's mission to support research in fields such as Applied and Computational Mathematics, Artificial Intelligence, Big Data Analytics, Cloud Computing, Cybersecurity, High-Performance Co…

SecureAI is the European Cybersecurity Competence Centre's dedicated topic for the security of AI systems themselves, and it is worth distinguishing carefully from the much larger population of Horizon Europe topics that apply AI to some other domain. The scope here is the attack surface of the models: adversarial attacks, backdoor injections and data poisoning are named explicitly, alongside privacy and robustness of AI models and systems more broadly. For teams working on model security, red-teaming, robustness certification, privacy-preserving machine learning or supply-chain integrity of training data, this is a rare topic where that work is the subject rather than a workpackage. The topic carries a budget of 21,200,000 euros and shares a deadline of 15 September 2026 at 17:00 CET with two sibling topics in the same ECCC call: HORIZON-CL3-2026-02-CS-ECCC-01 on approaches and tools for security in software and hardware development and assessment, budgeted at 20,000,000 euros and itself referencing AI-driven security testing methodologies, and HORIZON-CL3-2026-02-CS-ECCC-03 on advanced cryptographic schemes and high-assurance high-speed cryptographic implementations at 15,000,000 euros. Applicants weighing where a proposal fits should read all three topic texts, because the boundary between securing AI and using AI to secure software runs directly between topics 02 and 01. As with all Horizon Europe collaborative topics, proposals are expected from consortia spanning multiple Member States or Associated Countries rather than from single organisations, and evaluation is against the published topic-specific expected outcomes.

This ECCC topic funds security in the software and hardware development lifecycle, and it earns a place on an AI funding list for a specific reason: AI-driven security testing methodologies are named as a contribution area within scope. That makes it the natural home for work applying machine learning to vulnerability discovery, fuzzing, static and dynamic analysis, secure code generation and assessment, and automated assurance of hardware designs - work that often sits awkwardly between AI calls that want novel models and security calls that want no AI at all. It should be read alongside its sibling topic in the same call, HORIZON-CL3-2026-02-CS-ECCC-02 SecureAI, which covers the opposite direction: securing AI models and systems themselves against adversarial attacks, backdoor injections and data poisoning, with a budget of 21,200,000 euros. The boundary between using AI to secure software and securing AI runs precisely between these two topics, and choosing the wrong one is a common and costly proposal error. A third sibling, HORIZON-CL3-2026-02-CS-ECCC-03, covers advanced cryptographic schemes and high-assurance high-speed cryptographic implementations at 15,000,000 euros. All three share a deadline of 15 September 2026 at 17:00 CET. The topic budget here is 20,000,000 euros. As a Horizon Europe collaborative topic, proposals are expected from multi-country consortia rather than single organisations, and cybersecurity topics under Cluster 3 commonly carry additional participation restrictions relating to control by entities from non-associated third countries, so the topic conditions need reading in full before consortium building starts.