Optical simulators rank among the most promising candidates to power future technological breakthroughs in terms of speed, scalability, power-consumption and quantum advantage, serving a wide range of useful optimization problems. However, the operation of such simulators remains currently limited by noise, the extent of algorithmic problems they can embed and to the classical regime where they compete with supercomputers. HEISINGBERG aims to bring our state-of-the-art spatial photonic spin simulator (an iterated cycle of all-optical processing through a spatial light modulator that couples 10,000 spins) into the quantum regime by upgrading its coherent drive to squeezed light, making it fully programmable through vector-matrix multiplication schemes, use of holography, ancillary spins & effective magnetic fields, and designing dedicated custom-tailored and purpose-built algorithms. The reduced fluctuations in one quadrature of the fields will allow us to scale up and optimize the performances of the existing machine to bring it beyond the capabilities of both classical supercomputers and competing spin-simulators. HEISINGBERG devices will operate 100,000 spins at room temperature and process new quantum annealing algorithms on an improved XY architecture. Besides, the nonclassical resources of squeezed states when modulated, admixed and phase-controlled through beam splitters, such as entanglement or superpositions of multiphoton states will be prospected to harness a quantum advantage and boost our machine into its quantum simulation regime. This development will stimulate the quantum information processing community by concretely articulating problems of algorithmic complexity and clarify the nature of the quantum advantage available in annealers and simulators. These advances will allow us to demonstrate, on a cloud platform, annealing and adiabatic algorithms that can efficiently solve NP-hard problems.

AVALANCHE Vision: While technological solutions for investigations and global cooperation do exist, they are mostly fragmented and myopic focusing on providing very narrow and isolated functions within their own boundaries without ensuring interoperability and international cooperation. To alleviate the limitations of existing solutions, AVALANCHE aims to make transformative steps towards the development of a highly innovative, holistic, multi-disciplinary, high-tech, and versatile solution for significantly increasing/broadening the operational capabilities of LEAs in their struggle to detect, analyse, track, investigate and prevent cross-border illicit activities of high-risk criminal networks, migrant smuggling, firearms, drugs, child exploitation, terrorism, cyber and intellectual property crime coordinated through the digital world. Building on Pillars I and II, the AVALANCHE platform will offer tools for semi-automatic collection of evidence to foster explainable investigations and reasoning through intelligence-led methods and contextual-aware gleaning of actions. Also, building on Pillar III, the AVALANCHE platform will provide interoperable systems and interconnection with national and international databases through common standards, data and schemas alignment, and mediation to foster information exchange and international cooperation. To guarantee the wide SMEs solutions adoption by the actual practitioners, AVALANCHE will produce training curricula, benchmark with Europol’s Innovation Lab, contribute to LEAs operational standards and establish a broad ecosystem of crime-relevant stakeholders, and complement its objectives by continuously receiving guidance from the EU Policy Instrument (EMPACT). Finally, AVALANCHE will validate the integrated platform through a demonstration in diverse business scenarios of HP that cover key operational domains (from cross-border illicit activities to antisemitism, and more) with notable societal and market impact.

SECONDO addresses the question “How can decisions about cyber security investments and cyber insurance pricing be optimised?” SECONDO will support professionals who seek cyber security investments, developed to support human decision making, and a complete well-founded security strategy. This is a timely research problem, as the rapid growth of cyber-attacks is expected to continue its upwards trajectory. Such growth presents a prominent threat to normal business operations and the EU society itself. On the other hand, an interesting, well-known, finding is that an organisation's computer systems may be less secure than a competitor's, despite having spent more money in securing them. Budget setting, cyber security investment choices and cyber insurance, in the face of uncertainties, are highly challenging tasks with massive business implications. SECONDO aims to make impact on the operation of EU businesses who often: (i) have a limited cyber security budget; and (ii) ignore the importance of cyber insurance. Cyber insurance can play a critical role to the mitigation of cyber risk. This can be done by imposing a cost on firms' cyber risk through a premium that they have to pay and the potential for paying a smaller premium should they reduce their current cyber security risk. SECONDO has a cross-disciplinary nature, combining mathematical and engineering insights to empower innovative software. Apart from the novel research results, the project will offer a software platform to narrow the gap between theoretical understanding and practice. To achieve this, the four industrial project partners will i) lead the part of the project where industrial needs will be entered as input to the requirements collection phase, and, ii) provide their innovative software for risk assessment. The three academic partners will work together to i) design and thoroughly describe the proposed methodologies, but also ii) contribute to their software development.

The main objective of BigDataOcean is to enable maritime big data scenarios for EU-based companies, organisations and scientists, through a multi-segment platform that will combine data of different velocity, variety and volume under an inter-linked, trusted, multilingual engine to produce a big-data repository of value and veracity back to the participants and local communities. BigDataOcean aims to capitalise on existing modern technological breakthroughs in the areas of the big data driven economy, and roll out a completely new value chain of interrelated data streams coming from diverse sectors and languages and residing on cross technology innovations being delivered in different formats (as well in different states, e.g. structured/unstructured, real-time/batches) in order to revolutionise the way maritime-related industries work, showcasing a huge and realistic economic, societal and environmental impact that is being achieved by introducing an economy of knowledge into a traditional sector which does not operate in an orchestrated manner and is rather fragmented. This infrastructure will be combined with four strong pilots that will bring into BigDataOcean a huge amount of data (in TBs) in order to develop the largest maritime database as a resource of collaborative, data-driven intelligence. BigDataOcean will give participants the capability to upload both private and public resources of data, and interrelate them over public and private queries and diagrams. The BigDataOcean system backbone will be domain-agnostic and interoperable with the most popular and established data processing technologies and sensor types, and will be capable of conforming to various different operation systems that one can nowadays meet. Based on the consortium’s early market analysis, the project will break even and will be viable from its start (2020) and will return the initial investment of EU-commission by 2025 (ROI).

AEGIS, brings together the data, the network & the technologies to create a curated, semantically enhanced, interlinked & multilingual repository for public & personal safety-related big data. It delivers a data-driven innovation that expands over multiple business sectors & takes into consideration structured, unstructured & multilingual datasets, rejuvenates existing models and facilitates organisations in the Public Safety & Personal Security linked sectors to provide better & personalised services to their users. AEGIS will introduce new business models through the breed of an open ecosystem of innovation & data sharing principles. From the technology perspective, AEGIS targets to revolutionise semantic technologies in big data, big data analytics & visualisations as well as security & privacy frameworks by addressing current challenges & requirements of cross-domain & multilingual applications. The main benefits derived from AEGIS to data identification, collection, harmonisation, storage & utilisation towards value generation for these sectors will be: Unified representation of knowledge; Accelerated, more effective & value-packed cycles of intelligence extraction & of services & applications development; Introduction of novel business models for the data sharing economy & establishment of AEGIS as a prominent big data hub, utilising cryptocurrency algorithms to validate transactions & handle effectively IPRs, data quality & data privacy issues though a business brokerage framework. Based on an early market analysis, the Total Addressable Market of AEGIS is up to $31bn (€27.1bn); AEGIS is able not only to capture a portion of the market size, but also to expand the pie through creating additional uncaptured value based on small data integration in typical big data repositories & algorithms. Based on the same analysis, the project will break even & will be viable from its launch (2020) & will have a ROI investment of EU-commission in the first years.