Digital evidence is currently an integral part of criminal investigations, and not confined to pure cybercrime cases. Criminal behaviours like financial frauds, intellectual property theft, industrial espionage, and terrorist networks leverage the Internet and cyberspace. The very ubiquity of digital devices, e.g. smartphones, in modern society makes digital evidence extremely relevant for investigations about all kinds of criminal behaviour like murder, contraband activities, and people smuggling, to name a few. Due to its nature, the use of digital evidence in a court of law has always been challenging. It is critical that it should be accompanied by a proper chain of custody, guaranteeing its source and integrity. LOCARD aims to provide a holistic platform for chain of custody assurance along the forensic workflow, a trusted distributed platform allowing the storage of digital evidence metadata in a blockchain. Each node of LOCARD will be able to independently set its own permission policies and to selectively share access to digital evidence with other nodes when deemed necessary and upon proper authorization through fine-grained policies. LOCARD's modularity will also allow diverse actors to tailor the platform to their specific needs and role in the digital forensic workflow, from preparation and readiness, to collection, to analysis and reporting. LOCARD will have a crowdsource module to collect citizen reports of selected violations, a crawler to detect and correlate online deviant behaviour, and a toolkit for investigators that will assist them in collecting online and offline evidence. This will be powered by an immutable storage and an identity management system that will protect privacy and handle access to evidence data using a Trusted Execution Environment. Blockchain technology will not only guarantee that information about the evidence cannot be tampered with, but allow interoperability without the need for a trusted third party.

popAI is a 24 month Coordination and Support Action bringing together security practitioners, AI scientists, ethics and privacy researchers, civil society organisations as well as social Sciences and humanities experts with the purpose of consolidating knowledge, exchanging experience and raising awareness in the EU area, under a well-planned work methodology. The core vision of popAI is to foster trust in AI for the security domain via increased awareness, ongoing social engagement, consolidating distinct spheres of knowledge (including theoretical & empirical knowledge by academics & non-academics) and offering a unified European view across LEAs, and specialised knowledge outputs (recommendations, roadmaps, etc), while creating an ecosystem that will form the structural basis for a sustainable and inclusive European AI hub for Law Enforcement. popAI approaches the call requirements under a sustainable ecosystem perspective, aiming to create cross disciplinary ecosystem AI-LEA ethics hubs. First, we aim to utilize existing knowledge, but also an extensive set of studies, to identify and record the direct and indirect stakeholders of the "security and AI" setting, as well as their respective points of view (concerns, perceived opportunities, challenges). This recording aims to further delve into the dynamic interactions of these stakeholders and ensure appropriate gender and diversity representation in the participatory processes. This way popAI will tap into the rich knowledge of security practitioners, civil society organisations, and citizens, as well as Social Sciences and Humanities experts, to define appropriate interactions and material (e.g. talks, cross-disciplinary reports, workshops, online resources) that will allow co-creation within the ecosystem. Such interaction will empower a Positive Sum viewpoint when participating in innovation processes related to security and AI (from idea inception, to product development and application).

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

EFFECTOR aims to enhance maritime surveillance, improve decisions support, and foster collaboration of maritime stakeholders by implementing an Interoperability Framework and associated Data Fusion and Analytics services for Maritime Surveillance and Border Security that will allow faster detection of new events, better informed decision making, achievement of a joint understanding and undertaking of a situation across borders, allowing seamless cooperation between operating authorities and on-site intervention forces ensuring that all existing privacy and data protection rules are fully respected. Specifically, EFFECTOR will unlock the full capabilities of maritime surveillance systems and data sharing at tactical and strategic level by introducing applied solutions for enhanced border and external security, including the implementation of a multilayered data lake platform for end-to-end interoperability and data exploitation, the exchange of enhanced situational awareness pictures at different level with CISE and EUROSUR, the adoption of interoperability standards for exploiting data sources and systems currently underutilized in maritime environment and the demonstration of new concepts and tools for knowledge extraction, semantic representation, data fusion, analytics, and federated querying that can scale from local to regional and up to national and transnational level. The EFFECTOR solution will be tested, validated and demonstrated in real operational scenarios together with maritime authorities, End Users and practitioners in France, Portugal and Greece. The project will leverage on the developments, results and experience from current and previous research projects (EUCISE2020, MARISA, RANGER, PERSEUS, BLUEMASSMED), from National Procurement projects of CISE Nodes and Adaptors and on the CISE infrastructure of the End Users.