MAGNETO addresses significant needs of law enforcement agencies (LEAs) in their fight against terrorism and organised crime, related to the massive volumes, heterogeneity and fragmentation of the data that officers have to analyse for the prevention, investigation and prosecution of criminal offences. These needs have been identified after consulting with eleven different European LEAs –members of the MAGNETO consortium. In response, MAGNETO empowers LEAs with superior crime analysis, prevention and investigation capabilities, by researching and providing tailored solutions and tools based on sophisticated knowledge representation, advanced semantic reasoning and augmented intelligence, well integrated in a common, modular platform with open interfaces. By using the MAGNETO platform, LEAs will have unparalleled abilities to fuse and analyse multiple massive heterogeneous data sources, uncover hidden relationships among data items, compute trends for the evolution of security incidents, ultimately (and at a faster pace) reaching solid evidence that can be used in Court, gaining also better awareness and understanding of current or past security-related situations. In parallel, MAGNETO will spark an ecosystem of third-party solution providers benefiting from its open, modular and reusable architectural framework and standard interfaces. To achieve these objectives, MAGNETO will test and demonstrate its developments on five representative and complementary use cases (types of crime), under real-life operational conditions in the facilities of eleven different LEAs, keeping them continuously in the production loop, adopting an agile implementation methodology and a multi-disciplinary scientific approach, combining researchers with exceptional track records, officers with top-level operational know-how in law enforcement, recognised experts for legal and ethical compliance to EU and national standards, and qualified training experts for innovative curricula development.

Critical Energy infrastructures (CEI) protection and security are becoming of utmost importance in our everyday life. However, cyber and system-theoretic approaches fail to provide appropriate security levels to CEIs, since they are often used in isolation and build on incomplete attack models, resulting in silos-like security management fragmented operational policies. To face these challenges, DEFENDER will (i) model CEIs as distributed Cyber-Physical Systems for managing the potential reciprocal effects of cyber and physical threats (ii) deploy a novel security governance model, which leverages on lifecycle assessment for cost-effective security management over the time (iii) bring people at centre stage by empowering them as virtual sensors for threat detection, as first level emergency responders to attacks, or by considering workforce as potential threats. DEFENDER will adapt, integrate, upscale and validate a number of TRL 4-5 technologies and deploy them within a TRL7 integrated yet adaptable framework for CEI security, resilience and self-healing “by design”, with a view to address, detect, and mitigate cyber-physical threats. To this aim DEFENDER framework will combine a range of devices/technologies for situational awareness (fixed sensors like PMUs, mobile devices like drones and advanced video surveillance) (ii) intelligent processing for cyber-physical threat detection with (iii) a toolbox for incident mitigation and emergency response and (iv) Human-In-The-Loop for managing people interaction with CEI, while leveraging on blockchain technology for peer-to-peer trustworthiness. The effectiveness of DEFENDER will be extensively validated on a CEI lab emulator (RWTH, Germany) and on 4 real life demonstrators (in France, Italy and Slovenia) fully covering the overall energy value chain, ranging from a bulk generation plant (ENGIE SA), to a decentralized RES generation one (BFP), a TSO HV network (ELES), to a DSO network (ASM) and a business prosumer.