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Intelligence Network and Secure Platform for Evidence Correlation and Transfer (INSPECTr)

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 (EuroSciVoc)

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Keywords

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Programme(s)

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Topic(s)

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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.

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.

(opens in new window) H2020-SU-SEC-2018-2019-2020

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Coordinator

UNIVERSITY COLLEGE DUBLIN, NATIONAL UNIVERSITY OF IRELAND, DUBLIN
Net EU contribution

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.

€ 1 615 942,50
Address
BELFIELD
4 Dublin
Ireland

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Region
Ireland Eastern and Midland Dublin
Activity type
Higher or Secondary Education Establishments
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Total cost

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.

€ 1 615 942,50

Participants (19)

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