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.

The aim of our project is to train police officers’ on the procedure, through gamification technologies in a safe and controlled virtual environment. Essential tasks during the creation of LAW-GAME serious game are to virtualise and accurately recreate the real world. We will introduce an attractive approach to the development of core competencies required for performing intelligence analysis, through a series of AI-assisted procedures for crime analysis and prediction of illegal acts, within the LAW-GAME game realm. Building upon an in-depth analysis of police officers’ learning needs, we will develop an advanced learning experience, embedded into 3 comprehensive “gaming modes” dedicated to train police officers and measure their proficiency in: 1. conducting forensic examination, through a one-player or multi-player cooperative gaming scenario, played through the role of a forensics expert. Developed AI tools for evidence recognition and CSI and car accident analysis, will provide guidance to the trainee. 2. effective questioning, threatening, cajoling, persuasion, or negotiation. The trainee will be exposed to the challenges of the police interview tactics and trained to increase her emotional intelligence by interviewing a highly-realistic 3D digital character, advanced with conversational AI. 3. recognizing and mitigating potential terrorist attacks. The trainees will impersonate an intelligence analyst tasked with preventing an impending terrorist attack under a didactic and exciting “bad and good” multiplayer and AI-assisted game experience. The proposed learning experience focuses on the development of the key competences needed for successfully operating in diverse and distributed teams, as required by several cross-organisational and international cooperation situations. The learning methodology developed by the LAW-GAME consortium will be extensively validated by European end-users, in Greece, Lithuania, Romania, Moldavia and Estonia.

CREST aims to equip LEAs with an advanced prediction, prevention, operation, and investigation platform by leveraging the IoT ecosystem, autonomous systems, and targeted technologies and building upon the concept of multidimensional integration and correlation of heterogeneous multimodal data streams (ranging from online content to IoT-enabled sensors) for a) threat detection and assessment, b) dynamic mission planning and adaptive navigation for improved surveillance based on autonomous systems, c) distributed command and control of law enforcement missions, d) sharing of information and exchange of digital evidence based on blockchain, and e) delivery of pertinent information to different stakeholders in an interactive manner tailored to their needs. CREST will also provide chain-of-custody, and path-to-court for digital evidence. Human factors and societal aspects will also be comprehensively addressed, while information packages for educating the wider public on identifying threats and protecting themselves will be prepared and distributed.The platform development will adopt ethics and privacy by-design principles and will be customisable to the legislation of each member state. CREST will be validated in field tests and demonstrations in three operational uses cases: 1) protection of public figures in motorcades and public spaces, 2) counter terrorism security in crowded areas, and 3) Cross-border fight against organised crime (e.g. firearms trafficking). Extensive training of LEAs' personnel, hands-on experience, joint exercises, and training material, will boost the uptake of CREST tools and technologies. With a Consortium of 8 LEAs from 8 European countries, 7 research/academic institutions, 1 civil organisation, and 7 industry partners, CREST delivers a strong representation of the challenges, the requirements and the tools to meet its objectives.

In order to support the fight against radicalization and thus prevent future terrorist attacks from taking place, the CounteR project will bring data from disperse sources into an analysis and early alert platform for data mining and prediction of critical areas (e.g. communities), aiming to be a frontline community policing tool which looks at the community and its related risk factors rather than targeting and surveilling individuals. This is a key point in ensuring the privacy of citizens and the protection of their personal data, an issue that has been of great concern to policymakers and LEAs alike, who must balance the important work they do with the need to protect innocent individuals. The system will incorporate state of the art NLP technologies combined with expert knowledge into the psychology of radicalization processes to provide a complete solution for LEAs to understand the when, where and why of radicalization in the community to help combat propaganda, fundraising, recruitment and mobilization, networking, information sharing, planning/coordination, data manipulation and misinformation. Information gained by the system will also allow LEAs and other community stakeholders to implement prevention programs and employ counternarratives rather than relying solely on surveillance. The CounteR solution will cover a wide range of information sources, both dynamic (e.g. social media) and offline (e.g. open data sources) and combined with world-renowned expertise in radicalization processes and their psychology. The CounteR solution will allow LEAs to take coordinated action in real-time while also preserving the privacy of citizens, as the system will target “hotspots” of radicalization rather than individuals. In addition, the CounteR solution will support information sharing between European LEAs and foster collaboration between diverse agencies by providing an open platform which prioritizes harmonized information formats.

In order to address the fast-evolving challenges with respect to advanced forms of cybercrimes enabled by fully available state-of-the-art technologies (Crime-as-a-Service), there is a need for LEAs to form and apply cutting-edge collaboration frameworks that will break communication silos within the wider judicial ecosystem. These frameworks may span in numerous pillars, such as (i) regulated, privacy-preserving and easy sharing of information related to criminal activities enabling cross-border agency-to-agency collaboration in a transparent and explainable manner; (ii) joint criminal investigation further facilitated by beyond state-of-the-art tools enabling real-time collaboration and the full exploitation of distributed digital infrastructures to enhance cybercrime intelligence; (iii) exchanging different types of expertise (cybersecurity experts, forensics experts, lawyers and stakeholders from the judicial ecosystem, psychologists, social scientists) to realise cutting edge investigative approaches; and (iv) knowledge and best practices sharing with respect to trainings and cybercrime awareness. GANNDALF will set new grounds for the fight against advanced forms of cyber threats and cyber-dependent crimes; it will (i) realise cutting-edge agency-to-agency data sharing mechanisms, optimising the balance between transparency and privacy based on the needs of each LEA; (ii) deploy a modular, decision-support toolbox that will comprise not only ground-breaking technologies for collaborative investigation, prediction and identification of advanced forms of cyber threats, but also optimisation mechanisms enabling the full exploitation of these technologies; (iii) build on the above 2 offerings and deliver a customizable, collaborative crime investigation sandbox for scenarios, hypotheses analysis and crime investigation; and (iv) facilitate policy drafting, training and citizens’ engagement via innovative mechanisms that will realise the Cyber Hygiene 2.0 visiοn.