Objective
Law Enforcement Agencies (LEAs) across Europe face today important challenges in how they identify, gather and interpret terrorist generated content online. The Dark Web presents additional challenges due to its inaccessibility and the fact that undetected material can contribute to the advancement of terrorist violence and radicalisation. LEAs also face the challenge of extracting and summarising meaningful and relevant content hidden in huge amounts of online data to inform their resource deployment and investigations.
In this context, the main objective of the TENSOR project is to provide a powerful terrorism intelligence platform offering LEAs fast and reliable planning and prevention functionalities for the early detection of terrorist organised activities, radicalisation and recruitment. The platform integrates a set of automated and semi-automated tools for efficient and effective searching, crawling, monitoring and gathering online terrorist-generated content from the Surface and the Dark Web; Internet penetration through intelligent dialogue-empowered bots; Information extraction from multimedia (e.g. video, images, audio) and multilingual content; Content categorisation, filtering and analysis; Real-time relevant content summarisation and visualisation; Creation of automated audit trails; Privacy-by-design and data protection.
The project brings together industry, LEAs, legal experts and research institutions. It is expected that this collaboration will have significant impact on 1) ensuring the final system meets end-user LEA requirements, 2) enabling LEAs to access and examine terrorist generated content online bringing significant advantages to their operational capability, and 3) promoting industry’s enhanced understanding of operational LEA requirements and their market competitiveness in the field of online organised crime, terrorism and harmful-radicalisation.
Fields of science
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
Programme(s)
Funding Scheme
IA - Innovation actionCoordinator
BT5 6LE Belfast
United Kingdom
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Participants (18)
57001 Thermi Thessaloniki
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S1 1WB Sheffield
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50733 Koln
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
1000 Bruxelles / Brussel
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
00195 Roma
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08002 Barcelona
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80539 Munchen
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LA1 2RX Lancaster
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
10177 Athina
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92230 Gennevilliers
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Legal entity other than a subcontractor which is affiliated or legally linked to a participant. The entity carries out work under the conditions laid down in the Grant Agreement, supplies goods or provides services for the action, but did not sign the Grant Agreement. A third party abides by the rules applicable to its related participant under the Grant Agreement with regard to eligibility of costs and control of expenditure.
78140 VELIZY VILLACOUBLAY
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Legal entity other than a subcontractor which is affiliated or legally linked to a participant. The entity carries out work under the conditions laid down in the Grant Agreement, supplies goods or provides services for the action, but did not sign the Grant Agreement. A third party abides by the rules applicable to its related participant under the Grant Agreement with regard to eligibility of costs and control of expenditure.
92190 MEUDON
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WF1 3QP Wakefield
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1000 Bruxelles / Brussel
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08009 Barcelona
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Participation ended
D-81245 Muenchen
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
Participation ended
SE11 5EF London
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69120 Heidelberg
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.