The GuardAI project seeks to enhance the security of edge AI systems, addressing their critical vulnerabilities. Emphasis is placed on high-stakes domains, as outlined in the EU’s AI Act, where these systems, including drones, connected and autonomous vehicles, and network edge infrastructure, are becoming widespread and will play a pivotal role in making crucial decisions. These cutting-edge applications heavily rely on real-time decision-making and the processing of sensitive data, rendering them susceptible to various security threats and adversarial attacks. Therefore, the overarching objective of GuardAI is to develop the next generation of resilient AI algorithms tailored for edge applications. Leveraging cutting-edge technological advancements, the project will develop innovative solutions to ensure the integrity, security, and resilience of these systems, fostering trust, and accelerating the safe adoption of AI-driven technologies. A holistic contextual understanding will be integrated, enabling systems to adapt and make informed decisions in dynamic environments. Through a multi-disciplinary and multifaceted approach, by bringing together researchers, industry experts, government agencies, AI practitioners, and advanced threat analysis methods, and robust AI algorithms, GuardAI aspires to create a paradigm shift in AI security. The development of standardized evaluation criteria forges a path to certification frameworks, and real-world insights facilitate a systematic approach to ensuring security-by-design concepts. Embracing a holistic approach, GuardAI also examines ethical considerations in AI technology development to promote ethically sound digital landscapes. Overall, the project will strive to elevate the standards of secure AI systems through cutting-edge advancements and a comprehensive, collaborative approach.

COVID-X will bridge the collaboration divide between eHealth solution providers -with emphasis on lean startups and small and medium-sized enterprises (SMEs)-, and the healthcare professional system to fight COVID-19. The purpose is to boost an end-to-end agile validation programme of cutting-edge technology in three real-world clinical scenarios, located in hotspots of the pandemic: Italy, Spain and Sweden. The project will fast-track value streams between the two poles under consideration: 1) attract, invest and empower a community of European eHealth SMEs –the beneficiaries of an acceleration program, selected by open calls- that will provide market-ready fast, cost-effective and easily deployable sampling, screening, diagnostic and prognostic systems and/or data-driven services and tools, already certified with -or close to receive- the CE marking (type 1 of the call); 2) actively involve some of the most relevant hospitals of Europe that have the resources, critical mass and ambition to scale-up their capabilities in the COVID-19 response; thanks to the support of an innovative data sandbox, released as an in-house asset of COVID-X, to facilitate access easily, uniformly and securely to various health data sources, and providing data services including Artificial Intelligence (AI)-based decision support systems, data security, visual analytics and intuitive dashboards capabilities. The project will invest dedicated efforts to enforce data privacy and security, ethical compliance and user acceptance. Besides a solid consortium to access world class startups/SMEs, deliver highly valuable technological & business services, provide an innovative data Sandbox with AI capabilities for COVID related services and access 3 piloting sites, COVID-X targets to attract +155 applications and select 31 to undertake through the COVID-X Programme, investing a total of €4.0mil in high impact solution providers.

The project aims to develop an innovative research and training programme to prepare next generation experts in critical entities resilience design. Fifteen doctoral candidates will collectively engage in an ambitious interdisciplinary research project focusing on aspects related to the resilience design, real-time monitoring and control, anomaly detection and isolation, and incident response, in geographically distributed systems of cyber-physical systems. The PhD topics will investigate open research questions about the use of systems and control theory, formal methods, explainable AI, data-driven approaches, and human-centered design to build safe and resilient societal-scale critical entities. The project will also promote industrial excellence by offering opportunities to the researchers for testing their tools and frameworks in real-world scenarios, provided by the industrial partners. In this line, industrial partners will provide scenarios focusing on water, energy and transportation services, inspired by a real deployment using state-of-the-art and innovative IoT components. The research outcomes that will be validated in the context of these use cases will be reusable with other critical entities in other sectors.

The REBECCA proposal aspires to tap into the potential of Real-world Data (RWD) for supporting groundbreaking clinical research on complex chronic conditions (CCC) as a complement to Randomised Controlled Trials (RCT). REBECCA moves beyond the analysis of Electronic health records (EHR), by combining it with detailed monitoring data from multiple wearable, online behaviour and registry data to monitor patients’ functional, emotional and Quality of Life trajectories, with high temporal granularity. REBECCA also proposes explainable causal modelling combined with deep learning to account for observed and latent confounders in RWD analysis. The project will focus on the complex array of chronic comorbidities developed during breast cancer recovery, in particular studying the impact of primary and adjuvant cancer treatment on patients’ quality of life and assessing the value of detailed patient monitoring as a means for improved patient care, but will also demonstrate the extensibility of REBECCA to other forms of cancer. To this end, a total of seven studies in Sweden, Norway and Spain will produce new knowledge on clinical management of cancer patients that will shape future guidelines and practices for post-cancer treatments. Best practices resulting from the REBECCA studies will be disseminated to researchers, public health and regulatory bodies throughout Europe to facilitate wider adoption of RWD in clinical research. In addition, the REBECCA platform, capable of detailed monitoring and privacy-preserving federated cross-country data analysis, will provide an infrastructure for continued progress on use of RWD beyond the end of the project. Through these activities, REBECCA aims at the mass adoption of RWD for understanding CCCs and ultimately at establishing RWD as a valuable clinical research and patient management tool.

The 6G vision for an open, distributed and user-centric evolution of the current SBA core network creates many security challenges and risks. The disaggregated heterogeneous cloud continuum (i.e. distributed cloud system with many stakeholders located in different regions, while private, public, or hybrid clouds are considered for the formation of the continuum), in conjunction with softwarization and IT-based infrastructure operations, set the stage for risks and challenges to trustworthiness in the 6G era. On top of the open and distributed 6G core over the edge-cloud continuum, SAFE-6G proposes a holistic research approach aimed to design, develop and validate a 6G-ready native trustworthiness framework by enabling user-centric safety, security, privacy, resilience, reliability functions. By utilizing (X)AI/ML techniques to cognitively coordinate and balance these functions, in order to optimize the Level of Trust (LoT), which realises the trust requirements and data governance policy that each user/tenant/human-role specifies, a feature that is considered an essential KVI for user-centric 6G. The proposed SAFE-6G framework covers the whole trustworthiness 6G lifecycle by applying trustworthiness analysis, realisation and post-evaluation during the whole user-centric service provision, from onboarding and deployment to operation and decomposition. Verification and validation of the proposed SAFE-6G framework will be performed at the Stream C SNS 6G-SANDBOX Athens platform using two Metaverse-based pilots. The immersive-applications will be tested considering different 6G system setups, different service flavors and deployments, under various threats and attacks.