Opendata, web and dolomites

KRAKEN SIGNED

Brokerage and market platform for personal data

Total Cost €

0

EC-Contrib. €

0

Partnership

0

Views

0

 KRAKEN project word cloud

Explore the words cloud of the KRAKEN project. It provides you a very rough idea of what is the project "KRAKEN" about.

mhmd    ensures    coupled    protection    models    usability    experiences    data    platform    ml    trading    national    industrial    grants    schemes    trade    personal    relying    strength    creates    utility    mpc    maturity    sharing    secure    preserving    stack    encryption    credential    abe    innovative    ledger    blockchain    centric    sovereignity    featuring    proposes    lessons    market    levels    plain    marketplace    cryptography    hence    deriving    processor    eidas    aggregated    fe    unprecedented    advantages    sovereign    leveraging    streamr    self    paradigms    offs    emergent    compatibility    sophisticated    suitable    tested    security    cloud    mainstream    proxy    assurance    services    mature    technologies    granting    ready    identity    incorporate    alternative    proving    metadata    paradigm    brokerage    provider    distributed    ai    subject    convenient    crypto    tools    analytics    claims    he    protect    metrics    privacy    kraken    compliant    trust    schemas    conveyed    subjects    techniques    learned    platforms    implementations    exist    decentralized   

Project "KRAKEN" data sheet

The following table provides information about the project.

Coordinator
ATOS SPAIN SA 

Organization address
address: CALLE DE ALBARRACIN 25
city: MADRID
postcode: 28037
website: www.atos.net

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Spain [ES]
 Total cost 5˙999˙787 €
 EC max contribution 5˙017˙662 € (84%)
 Programme 1. H2020-EU.2.1.1. (INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Information and Communication Technologies (ICT))
 Code Call H2020-ICT-2019-2
 Funding Scheme IA
 Starting year 2019
 Duration (year-month-day) from 2019-12-01   to  2022-11-30

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    ATOS SPAIN SA ES (MADRID) coordinator 506˙275.00
2    TECHNISCHE UNIVERSITAET GRAZ AT (GRAZ) participant 757˙500.00
3    AIT AUSTRIAN INSTITUTE OF TECHNOLOGY GMBH AT (WIEN) participant 661˙237.00
4    INFOCERT SPA IT (ROMA) participant 595˙000.00
5    STIFTUNG SECURE INFORMATION AND COMMUNICATION TECHNOLOGIES AT (GRAZ) participant 533˙425.00
6    LYNKEUS IT (ROME) participant 518˙000.00
7    FONDAZIONE BRUNO KESSLER IT (TRENTO) participant 425˙625.00
8    TX TECHNOLOGY EXPLORATION OY FI (HELSINKI) participant 393˙400.00
9    KATHOLIEKE UNIVERSITEIT LEUVEN BE (LEUVEN) participant 348˙250.00
10    XLAB RAZVOJ PROGRAMSKE OPREME IN SVETOVANJE DOO SI (LJUBLJANA) participant 278˙950.00

Map

 Project objective

KRAKEN Secure and privacy preserving platform (broKeRage And marKEt platform for persoNal data) aims to bring personal data sharing and trading at a level of maturity that does not yet exist, by leveraging on: i) the emerging paradigm of self-sovereign identity built upon a stack of distributed ledger technologies (multi-ledger) which ensures future compatibility with different specific blockchain implementations for identity management. It will provide a decentralized user-centric approach on personal data sharing and proving that it can incorporate the trust and security assurance levels deriving claims from national identity schemas (eIDAS-compliant); ii) tested data marketplace technologies which support data sharing as well as aggregated data sharing; iii) A set of different data protection techniques based on advanced crypto tools (P/F/HE, FE, MPC, ABE…) coupled with privacy preserving (AI/ML) analytics, featuring management of privacy / utility trade-offs and metadata privacy. iv) The project will provide market-ready tools and services with industrial strength and suitable privacy metrics that will be conveyed to data subjects with high usability. Taking advantages of the emergent models and lessons learned from previous experiences, including existing and mature cloud-based personal data platforms CREDENTIAL and MHMD, as well as Streamr marketplace services, Kraken proposes an unprecedented approach, which creates an alternative to mainstream paradigms while fully granting the privacy and self-sovereignity of the data subject. KRAKEN enables advanced, convenient data sharing control relying on innovative end-to-end encryption and use of sophisticated proxy cryptography schemes grants data subjects with unprecedented control over their data. Furthermore, this ensures that even the cloud provider (data processor) cannot access the data in plain-text and hence protect access to personal data. KRAKEN involves 10 partners and has a duration of 3 years.

Are you the coordinator (or a participant) of this project? Plaese send me more information about the "KRAKEN" project.

For instance: the website url (it has not provided by EU-opendata yet), the logo, a more detailed description of the project (in plain text as a rtf file or a word file), some pictures (as picture files, not embedded into any word file), twitter account, linkedin page, etc.

Send me an  email (fabio@fabiodisconzi.com) and I put them in your project's page as son as possible.

Thanks. And then put a link of this page into your project's website.

The information about "KRAKEN" are provided by the European Opendata Portal: CORDIS opendata.

More projects from the same programme (H2020-EU.2.1.1.)

5G-COMPLETE (2019)

A unified network, Computational and stOrage resource Management framework targeting end-to-end Performance optimization for secure 5G muLti-tEchnology and multi-Tenancy Environments

Read More  

Hydroptics (2019)

Photonics sensing platform for process optimisation in the oil industry

Read More  

EVOLVE (2018)

HPC and Cloud-enhanced Testbed for Extracting Value from Diverse Data at Large Scale

Read More