Cryptographic technologies and encrypted channel communications have become a standard security pre-requisite among government and industry protocols, schemes and infrastructure. Practical quantum computing, when available to cyber adversaries, will break the security of nearly all modern public-key cryptographic systems. Practical quantum computing, when available to cyber adversaries, will break the security of nearly all modern public-key cryptographic systems. Consequently, all secret symmetric keys and private asymmetric keys that are now protected using current public-key algorithms, as well as the information protected under those keys, will be subject to exposure. This includes all recorded communications and other stored information protected by those public-key algorithms, the so-called Harvest Now Decrypt Later (HNDL) paradigm. Any information still considered to be private or otherwise sensitive will be vulnerable to exposure and undetected modification. Once exploitation of Shor’s algorithm becomes practical, protecting stored keys and data will require re-encrypting them with a quantum-resistant algorithm and deleting or physically securing “old” copies (e.g., backups). Integrity and sources of information will become unreliable unless they are processed or encapsulated (e.g., re-signed or timestamped) using a mechanism that is not vulnerable to quantum computing-based attacks. PQ-NEXT will focus on developing a comprehensive framework to facilitate the seamless transition to post-quantum cryptographic standards. This includes creating a catalog of PQC algorithms, maintenance tools, and a quantum programming language with advanced features like high-performance simulation and hybrid quantum-classical optimization, ensuring crypto-agility and security against quantum threats for large-scale pilots, targeting the financial, critical infrastructure, digital identities and telco industries.

WiseFood aims at developing smart digital applications that will empower citizens to make healthier and more sustainable food choices. It will leverage state-of-the-art Artificial Intelligence (AI) techniques and tools, combining the factual knowledge representation capacity of Knowledge Graphs with the natural language understanding, generation, and reasoning abilities of Large Language Models. These will allow us to build novel tools that democratize access to reliable food-related information and go beyond the current levels of personalization and contextualization offered by existing food recommenders. The developed applications will be user-friendly and integrate seamlessly into daily life, not requiring specialized IT skills or devices. Our goal is to bridge the divide between knowledge, intention, and action with end-to-end intelligent solutions. A human-in-the-loop approach with food domain experts, including nutritionists, will be applied to ensure alignment with national policies and guidelines. Living Labs implementing a multi-actor approach are foreseen to co-create the envisioned solutions. These will take place in three different countries, Ireland, Hungary, and Slovenia, with the latter being an already established and operational short food supply chain Living Lab. The outcomes of WiseFood will enhance the overall food ecosystem, by promoting healthier dietary habits, reducing the ecological footprint of food consumption, and fostering a culture of well-informed and eco-conscious citizens.

Data growth and availability as well as data democratization have radically changed data exploration in the last 10 years. Many different data sets, generated by users, systems and sensors, are continuously being collected. These data sets contain information about scientific experiments, health, energy, education etc., and they are highly heterogeneous in nature, ranging from highly structured data in tabular form to unstructured text, images or videos. Furthermore, especially online content, is no longer the purview of large organizations. Open data repositories are made public and can benefit more types of users, from analysts exploring data sets for insight, scientists looking for patterns, to dashboard interactors and consumers looking for information. As a result, the benefit of data exploration becomes increasingly more prominent. However, the volume and complexity of data make it difficult for most users to access data in an easy way. In this project we propose INODE – Intelligent Open Data Exploration. The core principle of INODE is that users should interact with data in a more dialectic and intuitive way similar to a dialog with a human. To achieve this principle, INODE will offer a suite of agile, fit-for-purpose and sustainable services for exploration of open data sets that help users (a) link and leverage multiple datasets, (b) access and search data using natural language, using examples and using analytics (c) get guidance from the system in understanding the data and formulating the right queries, and (d) explore data and discover new insights through visualizations. Our service offering is formed by and will initially respond to the needs of large and diverse scientific communities brought by our three use case providers: (a) Cancer Biomarker Research - SIB Swiss Institute of Bioinformatics, Switzerland, (b) Research and Innovation Policy Making - SIRIS, Spain, and (c) Astrophysics - Max Planck Institute for Extraterrestrial Physics, Germany.

Nowadays, cybercrime is one of the most relevant and critical threats to both the economy and society in Europe. Establishing efficient and effective ways to protect services and infrastructures from ever-evolving cyber threats is crucial for sustaining business integrity and reputation as well as protecting personal and sensitive data. To that end, the SHIELD project proposes a universal solution for dynamically establishing and deploying virtual security infrastructures into ISP and corporate networks. SHIELD builds on the huge momentum of Network Functions Virtualisation (NFV), as currently standardised by ETSI, in order to virtualise security appliances into virtual Network Security Functions (vNSFs), to be instantiated within the network infrastructure using NFV technologies and concepts, effectively monitoring and filtering network traffic in a distributed manner. Logs and metrics from vNSFs are aggregated into an information-driven Data Analysis and Remediation Engine (DARE), which leverages state-of-the-art big data storage and analytics in order to predict specific vulnerabilities and attacks by analysing the network and understanding the adversary possibilities, behaviour and intent. The SHIELD virtual security infrastructure can either used by the ISP internally for network monitoring and protection, but it can also be offered as-a-service to ISP customers; for this purpose, SHIELD establishes a “vNSF Store”, i.e. a repository of available virtual security functions (firewalls, DPIs, content filters etc.) from which the ISP customers can select the ones which best match their needs and deploy them to protect their infrastructure. This approach promotes openness and interoperability of security functions and offers an affordable, zero-CAPEX security solution for citizens and SMEs. Moreover, SHIELD services can be easily scaled up or down, configured and upgraded according to customers’ needs, as opposed to security solutions based on monolithic hardware.

HS4U offers an evidence-based approach extending standardized design and regulatory paradigms towards industry 5.0. The project is promoting principles of modularization, optimization, and smart systems engineering towards the detection, prevention, mitigation and management of large passenger and cruise ships. Hence, HS4U holistic solutions for stress relief over conditions of health crises prioritize the assessment of typical cruise designs and day-to-day tasks. Following its two use cases (CELESTYAL and COLUMBIA BLUE), and its 4U(nique) pillars approach for research, i.e.1.societal/human, 2.environmental, 3.technological, 3.legislation factors, it adopts and delivers state-of-the art ecosystem of technologies offering groundwork to rethink health and safety designs and frameworks. HS4U bridges cross-sectorial multidisciplinary expertise to cross-fertilize research findings and provide best practices, protocol/policy recommendation and a complete solution for crew training based on multi-player gaming. Validation of proposed technology and passenger behavioral model will be based on live experiments. Special HS4Us open source/FAIR offerings are, ⁃ Collaborative digital framework (CDF) for live interaction of crew/passengers and IoT edge devices on the ship based on co-robotics concepts and Artificial Intelligence mechanisms and models. ⁃ Viral Detection Sensor (VDS) that will be developed, tested, validated, delivered, patented and commercialized to offer online indication of the location of pathogenic airborne spreads in indoor environments. ⁃ “Robot-cabin” real-life demonstrator displaying evidence-based 4U solutions on the interoperability of smart, and innovative methods for ship systems effective and fast detection, prevention, mitigation and inter-compartment, intra-compartment management ensuring healthy ship operations and safe return to port over conditions of health crises.