Programme Category
Programme Name
Identifier Code
Call
Summary
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.
Detailed Call Description
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.
Call Total Budget
Financing percentage by EU or other bodies / Level of Subsidy or Loan
70%
Expected EU contribution per project: between €3.00 and €4.00 million
Thematic Categories
- Information and Communication Technologies
- Information Technology
- Justice - Security
- Research, Technological Development and Innovation
Eligibility for Participation
- Businesses
- Educational Institutions
- Large Enterprises
- Legal Entities
- Other Beneficiaries
- Small and Medium Enterprises (SMEs)
Eligibility For Participation Notes
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.
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.
Call Opening Date
Call Closing Date
National Contact Point(s)
National Cybersecurity Coordination Centre Cyprus (NCC-CY)
1 Andrea Chaliou, 1075 Engomi, Nicosia,
Telephone: 1447
Fax: +357 22693070
Email: info@ncc.cy
Website: https://ncc.cy/en/