SHASAI targets the HW/SW security and AI-based high risk systems intersection, aiming to enhance the security, resilience, automated testing, and continuous assessment of AI systems. The rising interest in these systems makes them attractive targets for threat actors due to their complexity and valuable data. Ensuring the security of AI systems involves safeguarding AI models, datasets, dependencies, and securing the underlying HW/SW infrastructure. SHASAI takes a holistic approach of AI system security throughout their lifecycle stages. At requirement definition, SHASAI provides an enhanced risk assessment methodology for secure and safe AI. At design, SHASAI will propose secure and safe design patterns at SW and HW level to achieve trustworthy AI systems. During implementation, SHASAI provides tooling for a secure supply chain of the system by analyzing vulnerabilities in SW / HW dependencies, detecting poisoned data and backdoors in pretrained models, scanning for software vulnerabilities, hardening hardware platforms, and safeguarding intellectual property. At evaluation, SHASAI offers a virtual testing platform with automated attack and defense test suites to assess security against AI and infrastructure-specific threats. In operation, AI-enhanced security services continuously monitor the system, detect anomalies, and mitigate attacks using AI firewalls and attestation methods, ensuring availability and integrity. The feasibility of SHASAI methods and tools will be demonstrated in 3 real scenarios: 1. Agrifood industry: Cutting machines. 2. Health: Eye-tracking systems in augmentative and alternative communication. 3. Automotive: Tele-operated last mile delivery vehicle. Their heterogeneity and complementarity maximize the transferability of solutions. SHASAI will contribute to scientific, techno-economic, and societal impacts as it aligns with the CRA, EU AI Act, NIS2 and CSA, sharing and commercializing methods and tools to ensure trustworthy AI components.

Telecommunication networks have become a critical infrastructure for economic growth and social prosperity. Current networks will be unable to face the future demands and their increasingly diverse set of services, users, applications and requirements what is forcing network operators to transform them. At the centre of this network transformation is the broad-scale deployment of Network Function Virtualization (NFV) and Software-Defined Networking (SDN). 5GTANGO puts forth the flexible programmability of 5G networks with i) a NFV-enabled Service Development Kit (SDK), ii) a Store with advanced validation and verification mechanisms for VNFs/Network Services qualification (including 3rd party contributions) and iii) a modular Service Platform in order to bridge the gap between business needs and network operational management systems. We propose an integrated vendor-independent platform where the outcome of the development kit, that is a packaged NFV forwarding graph, is automatically tested and validated in the Store for their posterior deployment with a customizable orchestrator compatible with common existing Virtual Infrastructure Managers (VIM) and SDN controllers in the market. This end-to-end ecosystem for the agile development and deployment of services realises an extended NFV DevOps model between service developers, telecom operators and vertical industries, increasing operational efficiency, facilitating the implementation and validation of new services and accelerating the adoption of NFV technologies. 5GTANGO system will be demonstrated in two vertical pilots: advanced Manufacturing and immersive Media. 5GTANGO will actively promote collaboration and try to influence the SDOs most relevant for the project such as ETSI NFV or IETF, as well as the key open source initiatives such as OSM and Open-O. It is also 5GTANGO’s ambition to make key contributions to the 5G-PPP Programme, the targeted KPIs and commits to work with its peer 5G-PPP projects.

The aim of our project is to train police officers’ on the procedure, through gamification technologies in a safe and controlled virtual environment. Essential tasks during the creation of LAW-GAME serious game are to virtualise and accurately recreate the real world. We will introduce an attractive approach to the development of core competencies required for performing intelligence analysis, through a series of AI-assisted procedures for crime analysis and prediction of illegal acts, within the LAW-GAME game realm. Building upon an in-depth analysis of police officers’ learning needs, we will develop an advanced learning experience, embedded into 3 comprehensive “gaming modes” dedicated to train police officers and measure their proficiency in: 1. conducting forensic examination, through a one-player or multi-player cooperative gaming scenario, played through the role of a forensics expert. Developed AI tools for evidence recognition and CSI and car accident analysis, will provide guidance to the trainee. 2. effective questioning, threatening, cajoling, persuasion, or negotiation. The trainee will be exposed to the challenges of the police interview tactics and trained to increase her emotional intelligence by interviewing a highly-realistic 3D digital character, advanced with conversational AI. 3. recognizing and mitigating potential terrorist attacks. The trainees will impersonate an intelligence analyst tasked with preventing an impending terrorist attack under a didactic and exciting “bad and good” multiplayer and AI-assisted game experience. The proposed learning experience focuses on the development of the key competences needed for successfully operating in diverse and distributed teams, as required by several cross-organisational and international cooperation situations. The learning methodology developed by the LAW-GAME consortium will be extensively validated by European end-users, in Greece, Lithuania, Romania, Moldavia and Estonia.

Smart city applications require pervasive and large-scale infrastructures, which include heterogeneous IoT devices and distributed information systems, thus posing interoperability and cost challenges. Interoperable solutions, exploiting fog/edge/cloud computing resources, are fundamental for fair competition, especially in public procurements, while costs savings are necessary to speed up the smart city innovation pace, by enabling more stakeholders to easily enter the market, especially SMEs. The Fed4IoT project faces the interoperability issue, focusing on large scale environments and addressing the problem at different and synergic levels: device, platform and information. The goal of the project is “Federating IoT and Cloud Infrastructures to Provide Scalable and Interoperable Smart Cities Applications by introducing novel IoT virtualization technologies” and will be pursued through the following steps: 1) select/integrate/improve existing IoT and cloud platforms, including oneM2M, FIWARE and 5G ETSI MEC, so as to establish a reference interoperability solution; 2) use such reference solution to build up a pool of federated IoT and fog/edge/cloud resources; 3) design novel device-level IoT virtualization technologies to create "IoT slices" formed by virtual IoT devices and computing resources, exploiting the federated resource pool; 4) support orchestration and programmability for optimal IoT virtual function deployment and Big Data processing; 5) integrate information coming from different IoT domains and other city sources; 6) integrate the system components. The project solutions will be technically validated by implementing four specific smart city applications, based on a federated EU/JP platform, deployed in real life systems in two EU and two JP cities. The Fed4IoT consortium will also actively support standardization activities (ETSI, oneM2M, ITU, ISO, etc.) and EU/JP initiatives (e.g., AIOTI and ITAC), where consortium members are already involved.

With anticipated exponential growth of connected devices, future networks require an open solutions architecture facilitated by standards and a strong ecosystem. Such devices need an easy interface to the connected network to request the kind of communication service characterized by guarantees about bandwidth, delay, jitter, packet loss or redundancy. In response, the network should grant the requested network resources automatically and program the intermediate networking devices based on device profile and privileges. Similar requirement also comes from business applications where application itself asks for particular network resources based on its needs. Software Defined Networking (SDN) and Network Function Virtualisation (NFV) provide promising combination leading to programmable connectivity, rapid service provisioning and service chaining. As a part of 5G PPP programme, VirtuWind will develop and demonstrate SDN & NFV ecosystem, based on open, modular and secure framework showcasing a prototype for intra-domain and inter-domain scenarios in real wind parks as a representative use case of industrial networks, and validate the economic viability of the demonstrated solution. The wind park control network has been chosen as a professional application in VirtuWind as wind energy has now established itself as a mainstream of sustainable energy generation. By envisioning lower capital expenditure and operational expenditure costs in control network infrastructure, VirtuWind will play important role in assisting wind energy sector to achieve cost reductions. Further applicability of VirtuWind solution in other industrial domains will bring multifold benefits in their communication networks. The VirtuWind consortium consists of strong industry and academic partners covering the whole value chain of programmable networks. The consortium is striving for a common vision of creating industrial capability of SDN/NFV in Europe.