Despite the tremendous socio-economic importance of Supply Chains (SCs), security officers and operators have still no easy and integrated way to protect their interconnected Critical Infrastructures (CIs) and cyber systems in the new digital era. CYRENE vision is to enhance the security, privacy, resilience, accountability and trustworthiness of SCs through the provision of a novel and dynamic Conformity Assessment Process (CAP) that evaluates the security and resilience of supply chain services, the interconnected IT infrastructures composing these services, and the individual devices that support the operations of the SCs. In order to meet its objectives, the proposed CAP is based on a collaborative, multi-level evidence-driven, Risk and Privacy Assessment approach that support, at different levels, the SCs security officers and operators to recognize, identify, model, and dynamically analyse advanced persistent threats and vulnerabilities as well as to handle daily cyber-security and privacy risks and data breaches. CYRENE will be validated in the scope of realistic scenarios/conditions comprising of real-life supply chain infrastructures and end-users. Furthermore, the project will ensure the active engagement of a large number of external stakeholders as a means of developing a wider ecosystem around the project’s results, which will set the basis for CYRENE large scale adoption and global impact.

The “Smart City” paradigm aims to support new forms of monitoring and managing of resources as well as to provide situational awareness in decision-making fulfilling the objective of servicing the citizen, while ensuring that it meets the needs of present and future generations with respect to economic, social and environmental aspects. Considering the city as a complex and dynamic system involving different interconnected spatial, social, economic, and physical processes subject to temporal changes and continually modified by human actions. Big Data, fog, and edge computing technologies have significant potential in various scenarios considering each city individual tactical strategy. However, one critical aspect is to encapsulate the complexity of a city and support accurate, cross-scale and in-time predictions based on the ubiquitous spatio-temporal data of high-volume, high-velocity and of high-variety. To address this challenge, MARVEL delivers a disruptive Edge-to-Fog-to-Cloud ubiquitous computing framework that enables multi-modal perception and intelligence for audio-visual scene recognition, event detection in a smart city environment. MARVEL aims to collect, analyse and data mine multi-modal audio-visual data streams of a Smart City and help decision makers to improve the quality of life and services to the citizens without violating ethical and privacy limits in an AI-responsible manner. This is achieved via: (i) fusing large scale distributed multi-modal audio-visual data in real-time; (ii) achieving fast time-to-insights; (iii) supporting automated decision making at all levels of the E2F2C stack; and iv) delivering a personalized federated learning approach, where joint multi modal representations and models are co-designed and improved continuously through privacy aware sharing of personalized fog and edge models of all interested parties.