National Cyber Hubs

Expected Outcome: Projects are expected to contribute to all the following expected outcomes: Effective and innovative methods for gathering, sharing and using large data sets in energy applications for the purpose of training AI models while ensuring privacy and security. Advanced and - wherever possible - open-source AI foundation models to support the digitalisation of the energy system, through improved grid observability, forecasting of supply and demand, advanced storage and renewables integration, demand side flexibility and energy efficiency. Enhanced cooperation, knowledge sharing and interoperability among energy system actors for secure and seamless data exchange. Advanced methodologies for AI model development ensuring that the results are FAIR (Findable, Accessible, Interoperable, Reusable) beyond the project ending, open source and accommodating for technology evolution. Scope: The quality of AI models depends strongly on the amount, quality, and representativeness of the data used for their training. Projects are expected to focus on developing, training and testing AI foundation models, using extensive data sets to accelerate the energy transition in key focus…

Expected Outcome: Projects under this topic will contribute to the following outcomes: Accelerate market expansion for European deep tech startups across EU regions and beyond by fostering collaboration and mutual support among European deep tech startup ecosystem actors; Interconnect top-tier tech startup and scaleup hubs embedded in research, technology and higher education ecosystems; Enable cross-border access to infrastructures, facilities, corporates, investors and talents to deep tech startups and scaleups, including those funded by the European Innovation Council (EIC); Enable more European deep tech startups, including women-led startups and scaleups, to succeed scaling into globally competitive companies; Strengthen less-connected innovation hubs by integrating them into a Europe-wide collaborative network; Boost private and public investment in deep tech ventures established within the participating innovation hubs. Scope: This action builds upon the EU’s strategic vision outlined in the EU Competitiveness Compass [1] , the EIC scaling strategy [2] , and the EU Startup and Scaleup Strategy [3] . It aligns with the objectives of strengthening Europe’s deep tech…

Expected Outcome: Project results are expected to contribute to some or all of the following expected outcomes: Improved skills, tools and training curricula for Police Authorities in Europe and Civil Society Organisations (or Non-Governmental Organisations) to work with at-risk groups to prevent persons from going missing. Those improved skills, tools and training curricula are to take into account European multicultural dimension, as well as legal and ethical rules of operation; Enhanced investigation tools and methodologies for Police Authorities in Europe to tackle cold cases in the context of missing persons, based on modern (forensic) technologies and criminology; Modern training curricula for Police Authorities, their improved cross-border cooperation and enhanced tools and methodologies to tackle new cases of missing persons; Enriched European common approaches applied by Police Authorities in Europe to fight the issue of missing persons relying on the synergy of technology, the latest socio-psychological knowledge learned from cases, as well as field experience of Police Authorities and entities dealing with victims, while fully respecting fundamental rights such as…

Expected Outcome: Project results are expected to contribute to all of the following expected outcomes: Police Authorities in Europe are empowered with modern, accessible and validated tools, methodologies and training curricula to anticipate and cope with the misuse of new and emerging technologies for criminal purposes, with the aim to facilitate prevention, detection, efficient data access and investigation of criminal offences in a lawful manner and with full respect of fundamental rights, including the right to protection of personal data and to privacy; Reinforced interdisciplinary collaboration at the European level through the establishment of partnerships among technologists, policymakers and Police Authorities, resulting in a holistic understanding of the challenges posed by emerging technologies and in sharing of best practices; Clear guidelines and frameworks are created, including on procedures and rules, that ensure lawful access to data, balancing the needs of security with respect for privacy and that foster a European approach to the related challenges for the police and the judiciary. Scope: New and emerging technologies (e.g., new communication technologies,…

Expected Outcome: Project results are expected to contribute to some or all of the following expected outcomes: Improved understanding of links between addictions and crime, including drivers of criminality; Innovative and effective solutions, including training curricula, for Police Authorities in Europe and relevant Civil Society Organisations (or Non-Governmental Organisations) to prevent addictions and related crimes, with a special attention to young people at risk; Evidence-based support to modernising European criminal justice system’s approach when dealing with addiction-related offenses; Novel approaches of collaboration between different stakeholders, primarily Police Authorities in Europe and Civil Society Organisations (or Non-Governmental Organisations), to increase communities’ addiction resilience, security and safety. Scope: A close and complex relationship exists between addictions, such as gambling, drug or alcohol use, and crime (e.g., criminals are often under the influence of drugs while committing crimes, gamblers or drug users commit crimes to pay for their debts or drugs). In this topic, successful proposals are expected to analyse the specific nexus…

Expected Outcome: Secure Data Sharing Framework: Develop standardised and encrypted communication mechanisms to facilitate seamless data exchange between civilian and military stakeholders. These mechanisms should align with GDPR and other EU regulatory requirements. Early Warning Systems (EWS): Establish a European-level EWS for cyber and hybrid threats. These systems should integrate real-time monitoring tools and predictive analytics to pre-emptively identify and neutralise cyber and hybrid threats targeting critical infrastructure. Collaborative Training Programmes: Design joint training programmes that incorporate AI and cybersecurity scenarios for both civilian (including law enforcement) and military personnel. These programmes should address sector specific needs and hybrid threat scenarios. Integrated Threat Detection Systems: Deploy unified threat detection systems leveraging AI, ZTA, and Digital Twins for cross-sectoral application, targeting current and emerging cyber and hybrid threats. Cross-Sector Security Standards: Develop harmonised cybersecurity standards for dual-use technologies to ensure interoperability and scalability across EU Member States and propose…

Objective: The general objective of “Cross-Border Cyber Hub platforms” is to strengthen capacities to analyse, detect and prevent cyber threats and to support the production of high-quality intelligence on cyber threats, notably through the exchange of data from various sources, public and private, as well as through the sharing of state of-the-art tools and jointly developing cyber detection, analysis, and prevention capabilities in a trusted environment. They should provide new additional capacity building upon and complementing existing SOCs and CSIRTs and other relevant actors. The platforms should act as a central point allowing for broader pooling of relevant data and CTI, enabling the spreading of threat information on a large scale and among a large and diverse set of actors (e.g., CERTs/CSIRTs, ISACs, operators of critical infrastructures). Cross-Border Cyber Hub platforms will contribute to enhancing and consolidating collective situational awareness and capabilities in detection and CTI, supporting the development of better performing data analytics, detection, and response tools, through the pooling of larger amounts of data, including new data generated internally by…