Project description
Big Data support for criminal investigations
Crime investigators work on the field – identifying, documenting, collecting, and interpreting evidence to solve complex cases. Today, more than ever before, they need to make sense of massive streams of heterogeneous data. The EU-funded PREVISION project will provide law enforcement agencies with advanced, almost-real-time, analytical support for multiple Big Data streams (coming from various data sources). The project will allow for building dynamic and self-learning knowledge graphs that will help investigators become more aware in these fields and better address hybrid security threats, i.e. threats that combine physical and cyber attacks. The project will organise five representative and complementary use cases, including the protection of public spaces and the fight of illicit trafficking of antiquities, in full compliance with privacy requirements, human rights and applicable law.
Objective
The mission of PREVISION is to empower the analysts and investigators of LEAs with tools and solutions not commercially available today, to handle and capitalize on the massive heterogeneous data streams that must be processed during complex crime investigations and threat risk assessments. With criminals being ever more determined to use new and advanced technology for their cause, the aim is to establish PREVISION as an open and future-proof platform for providing cutting-edge practical support to LEAs in their fight against terrorism, organised crime and cybercrime, which represent three major cross-border security challenges that are often interlinked. PREVISION provides advanced near-real-time analytical support for multiple big data streams (coming from online social networks, the open web, the Darknet, CCTV and video surveillance systems, traffic and financial data sources, and many more), subsequently allowing their semantic integration into dynamic and self-learning knowledge graphs that capture the structure, interrelations and trends of terrorist groups and individuals, cybercriminal organisations and organised crime groups, giving rise to enhanced situational awareness in these fields.
PREVISION has a pan-European engagement and support agenda for LEAs: ten (10) different LEAs and practitioners take part in its consortium, while additional ones (including Europol) have joined its external advisory board. A strong inter-disciplinary dimension, combining technological expertise with sociological, psychological, linguistic and data science models, will lead to a common strategic approach for predicting abnormal and deviant behaviour, radicalisation potential, threat risks for soft targets, and cybercrime trends at different timescales. PREVISION will conduct demonstrations on five representative and complementary use cases, under real-life operational conditions, in full compliance with fundamental rights and applicable legislation.
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)
- H2020-EU.3.7. - Secure societies - Protecting freedom and security of Europe and its citizens Main Programme
- H2020-EU.3.7.1. - Fight crime, illegal trafficking and terrorism, including understanding and tackling terrorist ideas and beliefs
- H2020-EU.3.7.8. - Support the Union's external security policies including through conflict prevention and peace-building
Funding Scheme
IA - Innovation actionCoordinator
106 82 ATHINA
Greece
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Participants (32)
80686 Munchen
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46014 Valencia
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61-612 Poznan
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
46145 OBERHAUSEN
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LT-01403 Vilnius
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
57001 Thermi Thessaloniki
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46022 Valencia
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Participation ended
013685 BUCURESTI
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75794 Paris
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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.
69365 Lyon
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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.
31058 Toulouse
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153 41 Aghia Paraskevi Athina
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
1016 BX Amsterdam
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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.
91080 Courcouronnes
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Dundalk Louth
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
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.
SW1X 7QA London
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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
6200 MD Maastricht
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1040 Nicosia
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
83000 Toulon
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69450 SAINT CYR AU MONT D'OR
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01010 Vitoria-Gasteiz
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LT-01106 VILNIUS
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101 77 Athens
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80539 Munchen
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10177 Athina
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MD - 2004 CHISINAU
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80539 Muenchen
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BT5 6LE Belfast
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060117 Bucuresti
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013685 Bucuresti
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2628 CN Delft
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