Enhancing the Security, Privacy and Robustness of AI Models and Systems (SecureAI)

Topic description

Expected Outcome: Proposals are expected to contribute to one or more of the following: Robust AI models and systems capable of resisting different classes of adversarial manipulation; Innovative defence mechanisms for AI models and systems against new attack families; Methodologies for detecting and mitigating attacks, such as data poisoning, backdoor exploitation and misclassification; AI systems leveraging privacy-enhancing technologies that maintain data confidentiality and regulatory compliance, enabling trusted in-house AI deployments (e.g., for governments and enterprises). Scope: The increasing reliance on AI in cybersecurity, critical infrastructure, and decision-making processes raises concerns about the security and robustness of AI systems. As AI systems become more prevalent, they are increasingly targeted by adversarial attacks that manipulate inputs, compromise training data, or introduce hidden vulnerabilities. This topic aims to strengthen the resilience of AI systems and algorithms against various threats and attacks, such as enhancing their resilience against adversarial attacks, backdoor injections, and data poisoning. Proposals should develop real-time anomaly detection, mitigation techniques to defend against adversarial attacks and robust federated learning techniques, in synergies with leading efforts on AI transparency, and in compliance with the AI Act. The topic is expected to: Develop robust AI models resistant to adversarial attacks. Exploring techniques to harden AI models and systems against adversarial perturbations, such as adversarial training, robust optimisation, and defence mechanisms that enhance the trustworthiness of AI. Improve detection of manipulated or poisoned training data. Advancing methodologies to identify and mitigate compromised datasets, leveraging techniques such as anomaly detection, provenance tracking, and automated data validation mechanisms. Address the concept of Private AI by developing mechanisms that enable AI models to be trained, deployed and operated in privacy-preserving environments, particularly for sensitive use cases, as for example for government and enterprise settings. This includes ensuring AI computations and data remain within trusted execution boundaries (e.g. on-premise or regulated cloud environments), and leveraging existing and emerging privacy-enhancing techniques such as federated learning, secure aggregation, computing on encrypted data, quantum-safe homomorphic encryption and secure inference in deep learning to safeguard the protection of personal and other sensitive data throughout the AI lifecycle.

Conditions and documents

General conditions 1. Admissibility Conditions: Proposal page limit and layout described in Annex A and Annex E of the Horizon Europe Work Programme General Annexes. Proposal page limits and layout: described in Part B of the Application Form available in the Submission System. 2. Eligible Countries described in Annex B of the Work Programme General Annexes. A number of non-EU/non-Associated Countries that are not automatically eligible for funding have made specific provisions for making funding available for their participants in Horizon Europe projects. See the information in the Horizon Europe Programme Guide . 3. Other Eligible Conditions In order to achieve the expected outcomes, and safeguard the Union’s strategic assets, interests, autonomy, and security, participation in this topic is limited to legal entities established in Member States and Associated Countries. In order to guarantee the protection of the strategic interests of the Union and its Member States, entities established in an eligible country listed above, but which are directly or indirectly controlled by a non-eligible country or by a non-eligible country entity, shall not participate in the action. described in Annex B of the Work Programme General Annexes. 4. Financial and operational capacity and exclusion described in Annex C of the Work Programme General Annexes. 5a. Evaluation and award: Award criteria, scoring and thresholds are described in Annex D of the Work Programme General Annexes. 5b. Evaluation and award: Submission and evaluation processes are described in Annex F of the Work Programme General Annexes and the Online Manual . 5c. Evaluation and award: Indicative timeline for evaluation and grant agreement described in Annex F of the Work Programme General Annexes. 6. Legal and financial set-up of the grants Eligible costs will take the form of a lump sum as defined in the Decision of 7 July 2021 authorising the use of lump sum contributions under the Horizon Europe Programme – the Framework Programme for Research and Innovation (2021-2027) – and in actions under the Research and Training Programme of the European Atomic Energy Community (2021-2025) [[This decision is available on the Funding and Tenders Portal, in the reference documents section for Horizon Europe, under ‘Simplified costs decisions’ or through this link: https://ec.europa.eu/info/funding-tenders/opportunities/docs/2021-2027/horizon/guidance/ls-decision_he_en.pdf ]]. described in Annex G of the Work Programme General Annexes. Specific conditions described in the [specific topic of the Work Programme] Some activities resulting from this topic may involve using classified background and/or producing of security sensitive results (EUCI and SEN). Please refer to the related provisions in section B Security — EU classified and sensitive information of the General Annexes. Application and evaluation forms and model grant agreement (MGA): Application form templates — the application form specific to this call is available in the Submission System Standard application form (HE RIA, IA) Evaluation form templates — will be used with the necessary adaptations Standard evaluation form (HE RIA, IA) Guidance HE Programme Guide Model Grant Agreements (MGA) Lump Sum MGA Call-specific instructions Detailed budget table (HE LS) Guidance: "Lump sums - what do I need to know?" Ownership Control Declaration Information on Security issues (Security section) Additional documents: HE Main Work Programme 2026-2027 – 1. General Introduction HE Main Work Programme 2026-2027 – 6. Civil Security for Society HE Main Work Programme 2026-2027 – 15. General Annexes HE Programme Guide Decision authorising the use of lump sum contributions under the Horizon Europe Programme Rules for Legal Entity Validation, LEAR Appointment and Financial Capacity Assessment EU Grants AGA — Annotated Model Grant Agreement Funding & Tenders Portal Online Manual Funding & Tenders Portal Terms and Conditions Funding & Tenders Portal Privacy Statement

Budget overview

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