Manufacturers of automated systems and the manufacturers of the components used in these systems have been allocating an enormous amount of time and effort in the past years developing and conducting research on automated systems. The effort spent has resulted in the availability of prototypes demonstrating new capabilities as well as the introduction of such systems to the market within different domains. Manufacturers of these systems need to make sure that the systems function in the intended way and according to specifications which is not a trivial task as system complexity rises dramatically the more integrated and interconnected these systems become with the addition of automated functionality and features to them. With rising complexity, unknown emerging properties of the system may come to the surface making it necessary to conduct thorough verification and validation (V&V) of these systems. VALU3S aims to design, implement and evaluate state-of-the-art V&V methods and tools in order to reduce the time and cost needed to verify and validate automated systems with respect to safety, cybersecurity and privacy (SCP) requirements. This will ensure that European manufacturers of automated systems remain competitive and that they remain world leaders. To this end, a multi-domain framework is designed and evaluated with the aim to create a clear structure around the components and elements needed to conduct V&V process through identification and classification of evaluation methods, tools, environments and concepts that are needed to verify and validate automated systems with respect to SCP requirements. The implemented V&V methods as well as improved process workflows and tools will also be evaluated in the project using a comprehensive set of demonstrators built from 13 use cases with specific SCP requirements from 6 domains of automotive, industrial robotics, agriculture, Aerospace, railway and health.

Ubiquitous AI will soon allow complex systems to drive on our roads, fly over our heads, move alongside us during our daily lives & work in our factories. In spite of this disruptive landscape, deployment and broader adoption of learned-enabled autonomous systems in safety-critical scenarios remains challenging. Continuous engineering (DevOps) can mediate problems when encountering new scenarios throughout the product life cycle. However, the technical foundations and assumptions on which traditional safety engineering principles rely do not extend to learning-enabled autonomous systems engineered under continuous development. FOCETA gathers prominent academic groups & leading industrial partners to develop foundations for continuous engineering of trustworthy learning-enabled autonomous systems. The targeted scientific breakthrough lies within the convergence of “data-driven” and “model-based” engineering, where this convergence is further complicated by the need to apply verification and validation incrementally & avoid complete re-verification & re-validation efforts. FOCETA’s paradigm is built on three scientific pillars: (1) integration of learning-enabled components & model-based components via a contract-based methodology which allows incremental modification of systems including threat models for cyber-security, (2) adaptation of verification techniques applied during model-driven design to learning components in order to enable unbiased decision making, & finally, (3) incremental synthesis techniques unifying both the enforcement of safety & security-critical properties as well as the optimization of performance. FOCETA approach, implemented in open source tools & with open data exchange standards, will be applied to the most demanding & challenging applications such as urban driving automation & intelligent medical devices, to demonstrate its viability, scalability & robustness, while addressing European industry cutting-edge technology needs.

Accelerated digitalisation in health sector brings opportunities for cost-effective and efficient delivery of personalised care, through medical devices (including software) connected to IT networks and increasingly combined with novel technologies (AI, cloud computing, blockchain or 5G networks) and simultaneously Europe is witnessing an increase in the complexity and sophistication of attacks threatening such critical infrastructure. CYLCOMED addresses the overall ambitious goal of strengthening the cybersecurity of connected, in vitro diagnostic and software as medical devices (CMDs, IVDs, SaMD), maintaining their performance and safety for patients and preserving or enhancing the confidentiality, integrity and availability of private data they exchange or allow to be remotely accessed and focusing on humans operating the technology as the weakest link in the chain for security and privacy, with training and awareness measures tailored to healthcare staff needs. It does so by enabling adoption by all ecosystem stakeholders of technologically sovereign and trustworthy cybersecurity methodologies and toolboxes for connected medical devices and the environments in which they are managed and operate (platforms), complemented with fit-for-purpose guidance covering identifed risks and gaps. It will further deliver: (i) risk assessment framework with risk benefit analyses schemes and (ii) toolbox addressing cybersecurity risks and gaps in connected medical devices;(iii) assessment and extension of baseline standards, best practices and guidelines covering challenges for CMDs including SW, making them fit for purpose when used in conjunction with novel technologies; (iv) demonstrations and case studies in relevant on premise hospital scenarios (COVID-19 patients monitoring) and remote telemonitoring scenarios improving the life of paediatric patients. CYLCOMED has 9 partners from 7 EU Member States and 1 associate partner from Switzerland and a duration of 36 months.