Money underpins all terrorist activities (without money propaganda, training, recruitment, and support are less effective or null). The disruption of terrorist financing activity is a key element in any fight against terrorism. DANTE will deliver effective, efficient and automated data mining, analytics solutions and an integrated system to detect, retrieve, and analyse huge amounts of heterogeneous and complex multimedia and multi-language (in five languages) terrorist-related contents from both the Surface and the Deep Web, including the Dark Nets. The ultimate goal is to discover (by “connecting the dots”), analyse and monitor potential terrorist-related activities and people, with focus on online fund raising activities, but also considering propaganda, training and disinformation. The challenging results of DANTE are achievable by exploiting, improving and integrating several existing data mining and analysis tools (mostly provided and owned by the partners; some already with high TRL). These tools and services will be further evolved and enhanced to be put at the service of the requirements provided by LEA partners (Guardia Civil, Policia Judiciaria, Home Office, Carabinieri). Thus, starting from lab and pre-prototype tools and methods, a market ready product with higher TRL will be the major outcome of DANTE. The presence of end user partners in the consortium will allow the validation/optimisation of the solution and boost of its adoption in their operational circumstances. The DANTE system will be validated and demonstrated in three pilots under the direct responsibility of the involved LEAs in their operational environments with the aim of detecting, analysing and monitoring terrorist-related contents for (i) propaganda (including recruitment, incitement, radicalization and disinformation), (ii) training and (iii) fund raising. DANTE surpasses the needs of the call for ensuring TRL6 of the projects results, by including components that will reach TRL7.

The Internet has become a key piece of any business activity. Criminal activity is not an exception. Some crimes previous to the Internet, such as thefts and scams, have found in the Internet the perfect tool for developing their activities. The Internet allows criminals hiding their real identity and the possibility to purchase specific tools for stealing sensitive data with a very low investment. The overall objective of RAMSES is to design and develop a holistic, intelligent, scalable and modular platform for Law Enforcement Agencies (LEAs) to facilitate digital Forensic Investigations. The system will extract, analyse, link and interpret information extracted from Internet related with financially-motivated malware. Customers, developers and malware victims will be included in order to obtain a better understanding of how and where malware is spread and to get to the source of the threat. To achieve these ambitious objectives, this project will rely on disruptive Big Data technologies to firstly extract and storage, and secondly look for patterns of fraudulent behaviour in enormous amounts of unstructured and structured data. We will focus on 2 case studies: ransomware and banking Trojans. In order to this, RAMSES brings together the latest technologies to develop an intelligent software platform, combining scraping of public and deep web, detecting manipulation and steganalysis for images and videos, tracking malware payments, extraction and analysis of malware samples and Big Data analysis and visualizations tools. Validation pilots will take place in three different EU countries (Portugal, Belgium and Spain) being the first a mono-LEA pilot in each site and the second a collaborative investigation pilot between several LEAs. Commercial potential will be validated during the project supported by a feasibility study to assess determinants for the adoption of the platform and appropriate business models.

ANITA will design and develop a novel knowledge-based user-centred investigation system for analysing heterogeneous (text, audio, video, image) online (Surface Web, Deep Web, DarkNet) and offline content for fighting illegal trafficking of drugs, counterfeit medicines, NPS and firearms. ANITA will combine a) innovative data source analysis of crypto-currency network and transactions and blockchain technologies; b) advanced Big Data analytics tools for automatic analysis of the vast amounts of multimodal content of the identified sources; c) sophisticated methodologies for capturing, modelling and inferring knowledge in human understandable forms (e.g. expressive ontologies), extracting also relevant and new knowledge from neural networks and formally storing it in the form of ontologies; d) development of an adaptive, cognitive user modelling framework that will capture, analyse, interpret, mimic and integrate key human cognitive and information processing functions for: i) incarnating the incorporation of human perception/cognition principles in the system processing pipelines (i.e. integrating the investigators ‘in-the-loop’ of the overall analysis process) and ii) facilitate the transfer of domain knowledge from the expert users to the novice ones; e) domain-related and user-oriented intelligence applications, which will enable users to identify patterns for spatial, temporal and causal correlations among illegal trafficking events, entities and activities and to support decision-making processes for countermeasures to undertake. All the above functionalities will be coupled and reinforced by an in-depth interdisciplinary analysis of the online illegal trafficking phenomenon (including the study of reaction strategies and countermeasures) and a thorough analysis of the online resources with respect to social, ethical, legal and privacy issues of concern. The proposed system capabilities will be demonstrated in multiple relevant operational environments.