Phoenix aims to develop a fundamentally novel computational model for reconstructing complex software systems, following some massive internal failure or external infrastructure damage. Recovering system operations is a challenging problem as it may require excessive system reconstruction using a different infrastructure (i.e., computational and communication devices named system cells) from the one that the system was originally designed for. Thus, software functionality may have to be remodularised and allocated onto devices with very different characteristics than the ones originally used but with some generic capabilities. Phoenix aims to develop a bio-inspired paradigm for reconstructing nearly extinct complex software systems based on a novel computational DNA (co-DNA) oriented systems modelling approach. The co-DNA will encapsulate logic and program code and will enable the use of analogues of biological processes for transmitting, transforming, combining, activating and deactivating it across computational and communication devices. The purpose of encoding the co-DNA of a system, and computational analogues of biological processes using it, is to enable other computational devices receiving the co-DNA to act as parts of the system that needs to be reconstructed, realise chunks of its functionality, and spread further the system reconstruction process. The Phoenix approach will bring a breakthrough in the current software system design and engineering paradigm. This will be through, not only a fundamentally new way of engineering mechanisms to support the resilience, continuity and recovery of software systems, but also the initiation of a new paradigm of designing and implementing software systems, based on the encoding of a system co-DNA that can trigger processes of self-regulated and incrementally expanding system functionality.

SEMIoTICS aims to develop a pattern-driven framework, built upon existing IoT platforms, to enable and guarantee secure and dependable actuation and semi-autonomic behaviour in IoT/IIoT applications. Patterns will encode proven dependencies between security, privacy, dependability and interoperability (SPDI) properties of individual smart objects and corresponding properties of orchestrations involving them. The SEMIoTICS framework will support cross-layer intelligent dynamic adaptation, including heterogeneous smart objects, networks and clouds, addressing effective adaptation and autonomic behaviour at field (edge) and infrastructure (backend) layers based on intelligent analysis and learning. To address the complexity and scalability needs within horizontal and vertical domains, SEMIoTICS will develop and integrate smart programmable networking and semantic interoperability mechanisms. The practicality of the above approach will be validated using three diverse usage scenarios in the areas of renewable energy (addressing IIoT), healthcare (focusing on human-centric IoT), and smart sensing (covering both IIoT and IoT); and will be offered through an open API. SEMIoTICS consortium consists of strong European industry (Siemens, Engineering, STMicroelectronics), innovative SMEs (Sphynx, Iquadrat, BlueSoft) and academic partners (FORTH, Uni Passau, CTTC) covering the whole value chain of IoT, local embedded analytics and their programmable connectivity to the cloud IoT platforms with associated security and privacy. The consortium is striving for a common vision of creating EU’s technological capability of innovative IoT landscape both at European and international level.

AERAS aims to develop a realistic and rapidly adjustable cyber range platform for systems and organisations in the critical healthcare sector, to effectively prepare stakeholders with different types of responsibility and levels of expertise in defending high-risk, critical cyber-systems and organizations against advanced, known and new cyber-attacks, and reduce their security risks. The platform will be a virtual cyberwarfare solution enabling the simulation of the operation and effects of security controls and offering hands-on training on their development, assessment, use and management. The platform will be based on an evidence-based approach where virtual cyberwarfare and simulations are configured according to evidence regarding: (i) the occurrence of cyber threats, and (ii) the effectiveness of the operation of the internal and external system defence mechanisms. Evidence will be collected by multi- faceted real-time monitoring and assessed according to Cyber Range Security Assurance (CRSA) models specifying potential cyber-attacks, the security mechanisms used against them, and the methods for assessing their effectiveness. The AERAS solution will be delivered at TRL-7 and validated through two different pilots in the healthcare sector: (i) a hospital medical systems pilot; and (ii) a public health systems pilot.

SYNAPSE aims to design, develop & deliver an Integrated Cyber Security Risk & Resilience Management Platform, with holistic Situational Awareness, Incident Response & Preparedness capabilities. The proposed platform will encompass: (i) Incident Response through process automation and orchestration mechanisms, also covering organisational/business aspects (e.g., business continuity processes); (ii) AI-enhanced Situational Awareness, encompassing extraction & analytics of actionable and pertinent Cyber Threat Intelligence (CTI), along with attack early warning & threat hunting systems; (iii) Preparedness through cybersecurity, privacy & business continuity training, covering different training delivery means, allowing it to tailor the delivery method to the content; (iv) Technical & economic risk management, integrating outputs of (i)-(iii) above and supporting risk-benefit analyses (including what-if scenarios) to inform decision-making and enable risk transfer schemes with Smart Contract-enabled cybersecurity insurance; (v) Continuous feedback between (i)-(iv) above, along with standards-based sharing, alerting & reporting (intra- & inter- Member State), based on outputs of (i)-(iii) above, thus enabling the establishment of shared situational awareness, coordinated response and joint preparedness

6G technologies, benefitting from softwarisation, Gb/s speed and sub-THz communications paradigms, open up opportunities for developing new and innovative network management strategies while navigating the evolution toward disaggregation, new software-based paradigms in architecting and operating future connectivity platforms, and embracing features of computing, automation and smartness, trust, privacy and security. Supported by this technology evolution, as the vision of new, smart and innovative capabilities is becoming a reality, superb user experience is expected even in presence of mobility and resource volatility. However, the fundamentally new and unknown features of advanced, disaggregated, virtualized and multi-vendor 6G based infrastructures, challenge the security and resilience design to the next level, by managing the unknown, complex and highly versatile infrastructures as they evolve. Indeed, the future deployment of 6G networks is inextricably connected with an integration of diverse hardware elements and infrastructures, thus leading not only to a highly heterogeneous environment, but also to functions and features that cannot be anticipated at the time of design. The vision of HORSE in this complex scenario, is to deal with the technology solutions, and system evaluation not yet foreseen, towards an omnipresent, smart and secure network service provisioning in the future network-of-networks landscape. To this end, HORSE proposes a novel human-centric, open-source, green, sustainable, coordinated provisioning and protection evolutionary platform, which can inclusively yet seamlessly combine advancements in several domains, as they get added to the system (e.g., predictive threats detection, proactive business-wise threats and breaches mitigation actions, programmable networking, semantic communications, Network Function Virtualisation (NFV), intent-based networking, AI-based techniques, cross-layer management of physical layer features, etc.).