The IoT market is currently undergoing transformation from applications involving semi-passive devices operating within a single platform, to applications involving smart objects with embedded intelligence while spanning multiple platforms. State-of-the-art security mechanisms are not sufficient for protecting end-to-end this wave of IoT applications. SecureIoT is a joint effort of global leaders in IoT services and IoT cybersecurity to secure the next generation of dynamic, decentralized IoT systems, which will span spanning multiple IoT platforms and networks of smart objects, through implementing a range of predictive IoT security services. SecureIoT will architect predictive security services in-line with leading edge reference architectures (RA) for IoT applications (i.e. RAs of the Industrial Internet Consortium, the OpenFog Consortium and the Platform Industrie 4.0), which will serve as a basis for specifying security building blocks at both the edge and the core of IoT systems. SecureIoT will provide concrete implementations of security data collection, security monitoring and predictive security mechanisms, which will be the basis for offering integrated services for risk assessment, compliance auditing against regulations and directives (e.g. GDPR, NIS, ePrivacy), as well as support to IoT developers based on programming annotations. The services will be open and based on the SECaaS (Security-as-a-Service) paradigm. The SecureIoT services will be challenged in market driven scenarios and use cases in the areas of smart manufacturing (Industrie 4.0), connected cars and IoT-enabled socially assistive robots. Their deployment will be based on both enterprise-scale globally available IoT platforms and community open source platform of the partners. As part of its exploitation strategy, SecureIoT will integrate a multi-sided market platform in order to offer SECaaS services, but also to enable integration of additional security mechanisms in its ecosystem.

PolicyCLOUD delivers a unique integrated environment addressing the full lifecycle of policy management: modelling, monitoring, enforcing, simulation, analysis and compliance. The environment will utilize the capabilities offered by the European Cloud Initiative, with an emphasis on data analysis to facilitate evidence-based policy making. PolicyCLOUD introduces a pioneering approach for the development of policies “collections” to exploit collective knowledge towards policy co-creation and cross-sector optimization. The co-creation of multi-modal policies will follow an innovative modelling process for structural representation of schema-based policies. PolicyCLOUD environment seamlessly integrates a methodology for utilizing cloud environments and data in policy making structures considering sociological, cultural, political, legal and economic properties. PolicyCLOUD environment will integrate a set of reusable models and tools, ranging from social dynamics and behaviour analysis, to situational knowledge acquisition, opinion mining and sentiment analysis, complemented with tools for data aggregation, linking and cleaning. Citizen participation will be ensured exploiting techniques for incentives management and a Living Lab approach put forward by PolicyCLOUD. A toolkit which allows the specification of transferable and re-usable analytics tasks in a declarative way, their integration in the policies management path, as well as an adaptive visualization environment, will realize PolicyCLOUD’s vision of openness and extensibility. Targeting high impact, PolicyCLOUD delivers a data marketplace enabling the creation of an entire ecosystem of stakeholders contributing, producing, processing and using policy-related data assets. The reusable models and tools and this marketplace provide the ground for the proposed dual-business plan, which has been compiled by the consortium to ensure the long-term sustainability and take-up of the PolicyCLOUD results.

AI systems in industrial plants must be safe, trusted and secure, even when operating in dynamic, unstructured and unpredictable environments. STAR is a joint effort of AI and digital manufacturing experts towards enabling the deployment of standard-based secure, safe reliable and trusted human centric AI systems in manufacturing environments. STAR will research and make available to novel technologies that will enable AI systems to acquire knowledge in order to take timely and safe decisions in dynamic and unpredictable environments. Moreover, it will research technologies that enable AI systems to confront sophisticated adversaries and to remain robust against security attacks. STAR’s will research and integration leading edge AI technologies with wide applicability in manufacturing environments, including: •Active learning systems that boost safety and accelerate the acquisition of knowledge. •Simulated reality systems that accelerate Reinforcement Learning (RL) in human robot collaboration scenarios. •Explainable AI (XAI) systems that boost the transparency of industrial systems and increase the trust on them. •Human Centric digital twins enabling worker monitoring for safer and trustful production processes. •Advanced RL techniques for optimal navigation of mobile robots and for the detection of safety zones in industrial plants. •Cyber-defence mechanisms for sophisticated poisoning and evasion attacks against deep neural networks operating over industrial data. These technologies will be validated in challenging scenarios in manufacturing lines in the areas of quality management, human robot collaboration and AI-based agile manufacturing. STAR will eliminate security and safety barriers against deploying sophisticated AI systems in production lines. The results will be fully integrated into existing EU-wide initiatives (EFFRA, AI4EU), as a means of enabling researchers and the European industry to deploy and leverage advanced AI solutions in production lines.

Despite rising investments on BigData, AI and IoT in finance/insurance, financial and insurance organisations are still facing many challenges (i.e. data “silos”, regulatory complexity, lack of testbed resources) in realizing the full potential of these technologies. INFINITECH is a joint effort of global leaders in ICT and finance towards lowering the barriers for BigData/IoT/AI driven innovation, boosting regulatory compliance and stimulating additional investments. It will provide: 1)Novel BigData/IoT technologies for seamless management and querying of all types of data (e.g., OLAP/OLTP, structured/unstructured/semi-structured, data streaming & data at rest), interoperable data analytics, blockchain-based data sharing, real-time analytics, as well as libraries of advanced AI algorithms. 2)Regulatory tools incorporating various data governance capabilities (e.g. anonymization, eIDAS integration) and facilitating compliance to regulations (e.g., PSD2, 4AMLD, MIFiD II). 3)Nine novel and configurable testbeds & sandboxes, each one offering Open APIs and other resources for validating autonomous and personalized solutions, including a unique collection of data assets for finance/insurance. The project’s results will be validated in the scope of 14 high impact pilots providing complete coverage of the sectors, including Know Your Customer (KYC), customer analytics, personalized portfolio management, credit risk assessment, preventive financial crime analysis, fraud anticipation, usage based insurance, agro-insurance and more. INFINITECH will establish a market platform that will provide access to the project’s solutions, along with a Virtualized Digital Innovation Hub (VDIH) that will support innovators (FinTech/InsuranceTech) in their BigData/AI/IoT endeavors. Based on their strong footprint in the European digital finance ecosystem, the partners will engage stakeholders from all EU-28 countries, making INFINITECH synonymous to disruptive BigData/AI innovation in the target sectors.