The underlyingassumption of the project proposal, in line with the UN Security Council recommendations (Resolution n. 2178, September 2014) and the Commission “European Agenda on Security”2015-2020(28.4.2015, COM(2015) 185 final), is that in order to contrast successfully violent extremism,what is neededis a more balanced response to terrorism,combining repressive (protective) measures with preventive measures, in a comprehensive approach in collaboration withactors of civil society and the communitiesof reference, based on a firm commitment to respecting fundamental rights, promoting integration, cultural dialogue and fighting discrimination. To this end, a better understanding of factors constituting violent radicalisation in Europe is needed, which aims,through a multidisciplinary analysis,to a comprehensive view of the phenomenon, investigatingits root causes, in order to develop appropriate countermeasures, ranging from early detection methodologies to strategies, ways and techniques of counter-narrative, involving LEAs together with experts and civil society actors at local, national and European level. In addition, it is necessary to acknowledge that violent radicalization,especially in the case of jihadist extremism,goesmainly through narratives that: have specific characteristics and contents; use specific communication codes;are addressed to specific audiences; and spread in a multitude of ways, over the Internet, as well as by means of in-person communication exchanges that take place in families, schools, places of worship, local communities, etc. These narratives havebeen proven effective towards vulnerable groups such as young people, detainees, and people craving for revenge after having experienced what they perceive as injustices, either at personal or group level. Furthermore, due to this multifarious background, such extremism is characterised by single or group terrorist acts also reflecting a variety of influences and motivational dr

PROPHETS will look at redefining new methods to prevent, investigate and mitigate cybercriminal behaviours through the development of a coherent, EU-wide, adaptive SECURITY MODEL, built upon the interplay of the human factors within the new cyber ecosystem and capable of addressing the four fundamental dimensions at the core of the phenomenon: 1. early identification of security threats; 2. investigations within a new public-private governance; 3. Increased complexity of the response due to the expansion of the security perimeter towards new societal fields and the emergence of challenging jurisdictional problems; and, last but not least, 4. perception of security and freedoms among citizens, which requires a new communication strategy for LEAs and security policy makers.

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.

LETS–CROWD will overcome challenges preventing the effective implementation of the European Security Model (ESM) with regards to mass gatherings. This will be achieved by providing the following to security policy practitioners and in particular, LEAs: (1) A dynamic risk assessment methodology for the protection of crowds during mass gatherings centred on human factors in order to effectively produce policies and deploy adequate solutions. (2) A policy making toolkit for the long-term and strategic decision making of security policy makers, including a database of empirical data, statistics and an analytical tool for security policies modelling, and (3) A set of human centred tools for Law Enforcement Agencies (LEAs), including real time crowd behaviour forecasting, innovative communication procedures, semantic intelligence applied to social networks and the internet, and novel computer vision techniques. LETS-CROWD will be a security practitioner driven project, fostering the communication and cooperation among LEAs, first responders, civil protection and citizens in the fight against crime and terrorism during mass gatherings by a set of cooperation actions. The project will put citizens at the centre of the research and will assess and evaluate how security measures affect them, and how they perceive them, while respecting EU fundamental rights. LETS-CROWD impact will be measured under practical demonstrations involving seven LEAs and relevant emergency services units. In order to facilitate the assessment of the performance, transferability, scalability and large scale deployment of these solutions, the demonstrations will be conducted following eleven use cases.