Project description
Breakthrough techniques against cybercrime and terrorism
Advanced technologies are increasingly used in criminal activities. Identifying, preventing and fighting modern crime demands the implementation of pioneering technologies and methods. The EU-funded AIDA project is focussing on cybercrime and terrorism by approaching specific issues related to law enforcement agencies (LEAs) using pioneering machine learning and artificial intelligence methods. The project will deliver a descriptive and predictive data analytics platform and related tools which will prevent, identify, analyse and combat cybercrime and terrorist activities. The platform is based on the fundamental technology applied to Big Data analytics provided with AI and deep learning techniques expanded and tailored with additional crime-specific capabilities and tools. The system will be delivered to LEAs through a safe sandbox environment, improving the technological readiness level in operational conditions with real data.
Objective
The proposed solution aims to deliver a descriptive and predictive data analytics platform and related tools using state-of-the-art machine learning and artificial intelligence methods to prevent, detect, analyse, and combat criminal activities. AIDA will focus on cybercrime and terrorism, by addressing specific challenges related to law enforcement investigation and intelligence. While cybercrime and terrorism pose distinct problems and may rely on different input datasets, the analysis of this data can benefit from the application of the same fundamental technology base framework, endowed with Artificial Intelligence and Deep Learning techniques applied to big data analytics, and extended and tailored with crime- and task- specific additional analytic capabilities and tools. The resulting TRL-7 integrated, modular and flexible AIDA framework will include LE-specific effective, efficient and automated data mining and analytics services to deal with intelligence and investigation workflows, extensive content acquisition, information extraction and fusion, knowledge management and enrichment through novel applications of Big Data processing, machine learning, artificial intelligence, predictive and visual analytics. AIDA system and tools will be made available to LEAs through a secure sandbox environment that aims to raise the technological readiness level of the solutions through their application in operational environment with real data.
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.
- social sciencespolitical sciencespolitical transitionsterrorism
- natural sciencescomputer and information sciencesdata sciencebig data
- social scienceslawlaw enforcement
- natural sciencescomputer and information sciencesdata sciencedata mining
- natural sciencescomputer and information sciencesdata sciencedata processing
Keywords
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
00144 Roma
Italy
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Participants (20)
2517 KK Den Haag
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57001 Thermi Thessaloniki
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S1 1WB Sheffield
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20009 Donostia San Sebastian
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
09128 Cagliari
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
46022 Valencia
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060071 Bucuresti
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28020 Madrid
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
637 00 Brno
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
1000-029 Lisboa
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
4 Dublin
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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.
10177 Athina
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
BT5 6LE Belfast
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28071 Madrid
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101 77 Athens
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020123 Bucuresti
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2595 CC The Hague
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1149-019 Lisboa
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15060 Tallinn
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