Technology advancements enhance everyday life, but they also provide numerous opportunities for the proliferation of advanced cybercrimes, which, via innovative tactics and techniques, pose serious security and financial risks to EU and beyond. ENSEMBLE aims to provide a well-rounded response to the fight against (cross-border) cybercriminal activities, at the nexus of advanced AI-based technological solutions, (multi-stakeholder) investigations processes, training, and awareness in order to detect and prevent cybercrime-related activities, with particular focus on ransomware, cyber fraud, data theft and extortion as well as unauthorised access and crypto-jackings. This will be achieved via a three-pillar approach. ENSEMBLE will develop a modular AI-based, forensically sound investigation toolbox based on user centric criteria, to assist Police Authorities in detecting, extracting, processing, and analysing online information relevant to cybercrime activities, thus fighting sophisticated cyber-threats, capitalising also in joint multi-stakeholder operations both at national and cross border level and in secure data and information sharing mechanisms. Police Authorities, prosecutors, and judicial actors involved in such investigations will be offered innovative training curricula and methods as well as synchronous and/or asynchronous learning methodologies that will be aligned to their needs and improve their current capacity, taking into consideration the technological, procedural, operational, legal/multi-jurisdictional dimensions. Finally, public awareness and engagement with relevant actors for early identification and prevention of cybercrimes will be cultivated through targeted awareness raising campaigns and specific policy recommendations. Having brough together a multidisciplinary team of five LEAs, seven research/academic institutions and six industry partners (including five SMEs) with a wide range of expertise in the field, ENSEMBLE provides a compelling

IAMI aims to revolutionize entity identification and resolution in security, intelligence, and investigation contexts. It addresses the challenges and limitations faced by current identification techniques and offers a visionary solution through advanced AI-powered software. The project's long-term vision is to propel EU LEAs and security/intelligence organizations into a new era of intelligence, investigation, and forensic capabilities. IAMI's core innovation is the development of an AI-powered software system that can seamlessly integrate with existing case management systems and analytic tools. At the heart of IAMI is the concept of the 'Identity-Attributes-Matrix (IAM)', a 3D construct that encompasses a broad spectrum of multi-modal identity-related attributes, including biometric data, non-biometric identity-related data, and analytic results. These attributes are used to facilitate large-scale entity identification/resolution, including a broader range of entity types, simultaneous and rapid multi-entity identification/resolution, systematic and continuous analysis of flux of probe attributes, confidence in noisy/corrupted probe data, reduced false positive rates, access to contact attributes, and the ability to classify fake identities and bots/avatars. Furthermore, IAMI sets the groundwork for effective collaboration and data sharing across European agencies, including international organizations like EUROPOL and INTERPOL through the establishment of a new EU-Wide IAMI enrolled data collection repository for terrorist threat assessment and awareness which enriches their capabilities and assets. The realization of IAMI's vision will be achieved through the demonstration of the developed IAMI solution. It will be communicated and disseminated among EU LEAs and security/intelligence agencies through project activities, including deliverables, training curricula, workshops, and pilots. IAMI represents a significant step forward in EU fight against terrorism.

Combatting frauds on identity and travel documents is a key mission of law enforcement agencies and border guards. Industries have been working on new means to combat frauds on identity, and public authorities are using numerous technologies to accomplish their mission, but permanent innovation is required to fight highly skilled defrauders. A number of European innovation projects have tested new ways to combat fraud but few of them reached an operational level. EINSTEIN objectives is to enhance significantly existing public authorities’ means through innovation, building on technologies proven in the labs but not mature for an operational usage yet. EINSTEIN will deliver six applications essential to fight identity frauds: 1) online ID issuance using a secure cloud-based server for real-time biometric quality checks and fraud detection, 2) mobile document and identity checks using commercially available smartphones, 3) document authentication module to detect fraudulent documents, 4) pre-registration for land-border crossings including biometrics and DTC, 5) EES kiosk with advanced fraud detection using video surveillance, 6) fast track for enrolled travelers using on-the-move face and iris. To ensure TRL7 at a minimum, practitioners will run six different pilot use cases in their own environment. A key objective is also to ensure interoperability and flexibility of all the components developed in the project so that they can be reused in different contexts, possibly by different providers. Design of open, well-defined, standardized interfaces will allow achieving this objective. Privacy being an essential concern of all European citizens and governments, EINSTEIN will take into account privacy-by-design principles, developing flexible components to ease their customization in order to meet not only the European legislation on data protection but also national legislations on this matter, which vary significantly from one country to the other.

ARMADILLO aims to equip Law Enforcement Authorities (LEAs) and more particularly, Police Authorities and Forensic Institutes, with a holistic, ground-breaking, easy-to-use, portable toolset that rapidly detects GHB concentrations in urine, saliva and beverages. To realize this, the project will focus on the design and development of in-situ GHB detection systems, integrating advanced optical spectroscopy and electrochemical techniques for precise GHB identification in the different matrices. Both optical and electrochemical detection techniques will be integrated to portable readers capable of quantitative GHB on-site determination. The optical spectroscopy techniques will explore surface-enhanced signal-based approaches (Raman and fluorescence) alongside paper strip methods, while electrochemical detection will combine a specialized fluidics module and NAD/NADH electrodes. In parallel, GHB-specific antibodies will be developed aiming to further enhance its detection selectivity and accuracy. The project will prioritize the enhanced collection and sharing of forensic evidence, emphasizing on forensics' data management and ensuring interoperability and harmonization across systems. By integrating data fusion mechanisms, it will provide reliable, safe, and court-proof forensic evidence, while also leveraging the potential of AI for refined Raman analysis. Concurrently, it will undertake a comprehensive risk assessment to bolster prevention strategies against drug-facilitated violence and assault, all while standardizing user interfaces and employing advanced visualization and reporting techniques. In order to avoid clinical trials and comply with the ethical considerations including the privacy and safety of any involved human subject, ARMADILLO will assess the accuracy, sensitivity and specificity of its sensing technologies using synthetic samples that simulate a wide range of GHB concentrations in urine and saliva samples.

TENSOR will provide LEAs a platform that facilitates the biometric evidence extraction, sharing and storage in cross border environments allowing them to share best practices in an automated, robust, secure, privacy-preserving and scalable manner. In addition, the full potential of biometrics technologies will be exploited and their fusion in case of partial evidence gathered in the crime scenes by forensic institutes strengthening their acceptance in the court of justice. More particularly, TENSOR will equip security practitioners with novel tools focusing on (a) Extraction of biometrics and other more or less distinctive features validated in forensic conditions that assist LEAs in identification, identity verification, intelligence and investigation processes and can be leveraged to unlock criminals’ mobile devices; (b) Sharing of biometrics through secure, automated, scalable exchange of biometric intelligence and court-proof evidence among LEAs in a cross-border manner, enhancing interoperability among legacy systems owned by security practitioners and Forensic Institutes; and (c) Storage of biometrics in a privacy-preserving way through a biometric data protection mechanism enabling revocability of biometric templates. TENSOR will also introduce the one-of-its-kind European Biometric Data Space creating a common ground among LEAs, Forensic Institutes and Security Researchers assisting in the faster adoption of modern biometric solutions.