Project description
Machine learning tools and techniques to fight child sexual exploitation
The distribution of child sexual exploitation materials is an abhorrent crime. Online service providers' and users’ suspicious material detection technologies are improving. However, the huge amount of referrals collected by law enforcement agencies (LEAs) in combination with limited human resources, manual analysis and the 4 000 % increase in referrals since 2014 prevent their investigative capacity. The EU-funded GRACE project will apply proven techniques in machine learning to the referral and analysis elaboration while appropriately managing the technical, ethical and legal challenges unique to fighting child sexual exploitation. The project will use resources from EUROPOL and its nine Member State LEAs to provide early, frequent and flexible results that will be handed back to EUROPOL and Member State LEAs, helping to ensure their future technological autonomy.
Objective
The use of the Internet to distribute CSEM is an abhorrent crime. Referrals from Online Service Providers are key to fighting CSE. OSPs, detection technologies and users reporting suspicious material are improving. However, this leads to an increase in the sheer volume of referrals coupled with the increase in the distribution of CSEM online that is pushing MS LEAs to their limits and affecting their their capacity to prevent harm to infants and children, rescue those in immediate danger, and investigate and prosecute perpetrators. The NCMEC process has improved LEA capability. But, a typical CSE case contains 1-3 TBs of video, 1–10 million images. Limited human resources, manual analysis and the 4,000% increase in referrals since 2014 obligates a new approach. GRACE will apply proven techniques in ML to the referral and analysis process while embracing the very technical, ethical and legal challenges unique to fighting CSE. GRACE will leverage resources already in place at EUROPOL and its 9 MS LEAs and attempt to provide results early, frequently and flexibly, prioritising easy wins in the research plan (e.g. deduplication). By applying Federated Learning approach to the challenge of optimising analysis and information flow, GRACE will enable cooperation between LEAs in improving their own capabilities and harness experiential knowledge. The results of GRACE will be handed back to EUROPOL and MS LEAs for unrestricted use in their missions, helping to ensure their future technological autonomy.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
- natural sciences computer and information sciences internet
- social sciences economics and business business and management commerce e-commerce
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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H2020-EU.3.7. - Secure societies - Protecting freedom and security of Europe and its citizens
MAIN PROGRAMME
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H2020-EU.3.7.1. - Fight crime, illegal trafficking and terrorism, including understanding and tackling terrorist ideas and beliefs
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H2020-EU.3.7.8. - Support the Union's external security policies including through conflict prevention and peace-building
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
RIA - Research and Innovation action
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) H2020-SU-SEC-2018-2019-2020
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
20009 Donostia San Sebastian
Spain
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Participants (22)
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D8 Dublin
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1050 Bruxelles / Brussel
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S1 1WB Sheffield
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57 001 THERMI THESSALONIKI
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28071 Madrid
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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.
Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
28040 Madrid
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50733 Koln
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The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.
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1081 Nicosia
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75800 Paris
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81677 Munich
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00144 ROMA
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22006 Nicosia
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2517 KK Den Haag
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020123 Bucuresti
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1000 029 Lisboa
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02-624 Warszawa
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08303 Vilnius
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1120 Bruxelles / Brussel
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1149-019 Lisboa
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34 100 CHALKIDA
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.
Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
24004 Leon
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9723ZA GRONINGEN
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.