Project description
Taking a high-tech approach to solving high-tech crime
Cybercrime is a borderless crime that leverages technology and the internet to exploit businesses, communities and individuals. Law enforcement officers responsible for investigating cybercrime need to be equally able to access cutting edge technology to combat these crimes and to bring down criminal networks. The EU-funded INSPECTr project will integrate a range of high-tech approaches, including Big Data analytics, cognitive machine learning and blockchain technologies into a shared intelligence platform that will improve digital and forensic capabilities, and reduce the complexity and cost of cross-border collaboration. The platform will incorporate privacy and ethics by design principles, and will take into account relevant national and international legislation.
Objective
Intelligence Network & Secure Platform for Evidence Correlation and Transfer (INSPECTr). The principal objective of INSPECTr will be to develop a shared intelligent platform and a novel process for gathering, analysing, prioritising and presenting key data to help in the prediction, detection and management of crime in support of multiple agencies at local, national and international level. This data will originate from the outputs of free and commercial digital forensic tools complemented by online resource gathering .
Using both structured and unstructured data as input, the developed platform will facilitate the ingestion and homogenisation of this data with increased levels of automisation, allowing for interoperability between outputs from multiple data formats.
Various knowledge discovery techniques will allow the investigator to visualise and bookmark important evidential material and export it to an investigative report. In addition to providing basic and advanced (cognitive) cross-correlation analysis with existing case data, this technique will aim to improve knowledge discovery across exhibit analysis within a case, between separate cases and ultimately, between interjurisdictional investigations.
INSPECTr will deploy big data analytics, cognitive machine learning and blockchain approaches to significantly improve digital and forensics capabilities for pan-European LEAs.
INSPECTr intends to reduce the complexity and the costs in law enforcement agencies and related actors to use leading edge analytical tools proportionally and in line with relevant legislation (including fundamental rights), with extended options for multi-level and cross-border collaboration for both reactive and preventive policing and facilitate the detection/prediction of cybercrime operations/trends.
The final developed platform will be freely available to all LEAs.
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
RIA - Research and Innovation actionCoordinator
4 Dublin
Ireland
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Participants (19)
D8 Dublin
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00185 Roma
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2322 Nicosia
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
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1000 Bruxelles / Brussel
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15060 Tallinn
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75800 Paris
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1050 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.
LV-1026 Riga
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2500BZ The Hague
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0030 Oslo
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BT5 6LE Belfast
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020123 Bucuresti
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9712CP Groningen
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H91CR20 GALWAY
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
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.
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.
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.
Participation ended
1015 LAUSANNE
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2000 Antwerpen
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
1050 Bruxelles / Brussel
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