The proposed solution aims to deliver a descriptive and predictive data analytics platform and related tools using state-of-the-art machine learning and artificial intelligence methods to prevent, detect, analyse, and combat criminal activities. AIDA will focus on cybercrime and terrorism, by addressing specific challenges related to law enforcement investigation and intelligence. While cybercrime and terrorism pose distinct problems and may rely on different input datasets, the analysis of this data can benefit from the application of the same fundamental technology base framework, endowed with Artificial Intelligence and Deep Learning techniques applied to big data analytics, and extended and tailored with crime- and task- specific additional analytic capabilities and tools. The resulting TRL-7 integrated, modular and flexible AIDA framework will include LE-specific effective, efficient and automated data mining and analytics services to deal with intelligence and investigation workflows, extensive content acquisition, information extraction and fusion, knowledge management and enrichment through novel applications of Big Data processing, machine learning, artificial intelligence, predictive and visual analytics. AIDA system and tools will be made available to LEAs through a secure sandbox environment that aims to raise the technological readiness level of the solutions through their application in operational environment with real data.

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.

The project will combine for the first time a multi-role lighter-than-air (LTA) unmanned aerial vehicle (UAV) with an ultra-high resolution multi-sensor surveillance payload supporting border surveillance as well as search & rescue applications, and specifically rough terrain detection. The sensor payload will include synthetic aperture radar (SAR), laser detection and ranging (LADAR), shortwave/longwave infrared (SWIR/LWIR) and acoustic cameras for direct target detection, as well as optical and hyperspectral cameras for indirect detection (via vegetation disturbance). The project will use the ground-based infrastructure of border police units (command & control centres), innovative data models (to identify illegal crossing patterns and preferred routes) and advanced audio/video analytics and storage (to provide additional detection capabilities). The technology concepts will be validated in the field by 6 border police units (Greece, Bulgaria, Romania, Moldova, Ukraine, Belarus) covering 3 major illegal migration routes into Europe (Eastern Mediterranean, Western Balkan and Eastern Borders Routes), which represent 58% of all illegal border crossings detected and are also the most used for smuggling of drugs, weapons and stolen vehicles. The combined solution will provide high coverage, resolution and revisit time with a lower cost (4 EUR/kg/hr) than satellites and higher endurance (100 kg payload for 12 hours) than drones. Based on the field trial results, the consortium expects to develop a solution that can be deployed further by European border polices after project completion. The project will also involve the contribution of NGOs working with illegal migration and human right protection issues, as well as regulatory experts dealing with the ethics and privacy requirements of border surveillance solutions

A free, democratic and open EU provides endless opportunities for its people. However, growth is not without risk, especially in cyberspace, in the ubiquity of connected devices and rapid technological change. Criminality is also adapting, seeking opportunity and taking on new forms. CC-DRIVER will use a multidisciplinary approach from the domains of psychology, criminology, anthropology, neurobiology and cyberpsychology to investigate, identify, understand and explain drivers of new forms of criminality. We will focus on human factors that determine criminal behaviours such as cyber juvenile delinquency and adolescent hacking. Scientific investigation of drivers into cybercrime, impact of online disinhibition and the effect of youth decision-making processes will inform our evidence-based intervention, mitigation and deterrence strategies. Our measures will be designed to educate regarding criminality and to divert youth from crime. Our consortium will investigate “cybercrime-as-a-service”, its modalities, purveyors and trends so that Member States, stakeholders and citizens have a shared view of the dimensions of cybercriminality, its impact on our society and economy and what we, collectively and individually, can do to overcome them. We will produce a youth self-assessment online metric tool designed to help understand cybercriminal behaviour and to prompt positive pathways. We will also develop a self-assessment questionnaire so that SMEs, CSOs and other stakeholders can assess their vulnerability to cybercrime attacks. For LEAs, we will produce tools to gather evidence and investigate and mitigate cybercrime operations. We will produce policy templates for combatting online cybercriminality. We will deliver opportunities for EU LEAs to exchange knowledge and experiences with a view to fostering common European approaches and strengthening the European Security Union as an area of freedom, justice, security and, importantly, opportunity.