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SODA SIGNED

Scalable Oblivious Data Analytics

Total Cost €

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EC-Contrib. €

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Partnership

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Project "SODA" data sheet

The following table provides information about the project.

Coordinator
PHILIPS ELECTRONICS NEDERLAND BV 

Organization address
address: HIGH TECH CAMPUS 52
city: EINDHOVEN
postcode: 5656 AG
website: www.philips.com

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 Netherlands [NL]
 Project website http://www.soda-project.eu
 Total cost 2˙980˙610 €
 EC max contribution 2˙980˙609 € (100%)
 Programme 1. H2020-EU.2.1.1. (INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Information and Communication Technologies (ICT))
 Code Call H2020-ICT-2016-1
 Funding Scheme RIA
 Starting year 2017
 Duration (year-month-day) from 2017-01-01   to  2019-12-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    PHILIPS ELECTRONICS NEDERLAND BV NL (EINDHOVEN) coordinator 783˙121.00
2    ALEXANDRA INSTITUTTET A/S DK (AARHUS N) participant 802˙125.00
3    TECHNISCHE UNIVERSITEIT EINDHOVEN NL (EINDHOVEN) participant 589˙698.00
4    AARHUS UNIVERSITET DK (AARHUS C) participant 505˙140.00
5    GEORG-AUGUST-UNIVERSITAT GOTTINGENSTIFTUNG OFFENTLICHEN RECHTS DE (GOTTINGEN) participant 300˙525.00

Map

 Project objective

More and more data is being generated, and analyzing this data drives knowledge and value creation across society. Unlocking this potential requires sharing of (often personal) data between organizations, but this meets unwillingness from data subjects and data controllers alike. Hence, techniques that protect personal information for data access, processing, and analysis are needed. To address this, the SODA project will enable practical privacy-preserving analytics of information from multiple data assets using multi-party computation (MPC) techniques. For this data does not need to be shared, only made available for encrypted processing. The main technological challenge is to make MPC scale to big data, where we will achieve substantial performance improvements. We embed MPC into a comprehensive privacy approach, demonstrated in an ICT-14.b and a healthcare use case.

Our first objective is to enable MPC for big data applications by scaling the performance. We follow a use case-driven approach, combining expertise from the domains of MPC and data analytics. Our second objective is to combine these improvements with a multidisciplinary approach towards privacy. By enabling differential privacy in the MPC setting aggregated results will not leak individual personal data. Legal analysis performed in a feedback loop with technical development will ensure improved compliance with EU data privacy regulation. User studies performed in a feedback loop with our consent control component will make data subjects more confident to have their data processed with our techniques. Our final objective is to validate our approach, by applying our results in a medical demonstrator originating from Philips practice and in a use case arising from the ICT-14.b data experimentation incubators. The techniques will be subjected to public hacking challenges. The technical innovations will be released as open-source improvements to the FRESCO MPC framework.

 Deliverables

List of deliverables.
Use-case-specific legal aspects Documents, reports 2020-04-09 20:40:39
Differential Privacy Documents, reports 2020-04-09 20:40:32
User studies analysis Documents, reports 2020-04-09 20:43:08
Publication of hacking challenge Websites, patent fillings, videos etc. 2020-04-09 20:41:23
Proof-of-concept for results of tasks 1.3/2.3 Other 2020-04-09 20:41:56
Proof-of-concept for results of tasks 1.2/2.2 Other 2020-04-09 20:41:07
Use-case-specific algorithms Documents, reports 2020-04-09 20:43:00
Special Purpose MPC Protocols Documents, reports 2020-04-09 20:42:18
Distributed/streaming algorithms Documents, reports 2020-04-09 20:42:28
General MPC Framework Documents, reports 2020-04-09 20:42:05
WP1 State of the art Documents, reports 2020-02-19 17:02:47
WP2 State of the art Documents, reports 2020-02-19 17:02:47
Public website Websites, patent fillings, videos etc. 2020-02-19 17:02:47
User studies plan Documents, reports 2020-02-19 17:02:47
General legal aspects Documents, reports 2020-02-19 17:02:47

Take a look to the deliverables list in detail:  detailed list of SODA deliverables.

 Publications

year authors and title journal last update
List of publications.
2018 Veeningen, M.; Chatterjea, S.; Horváth, A.Z.; Spindler, G.; Boersma, E.; Spek, van der, P.; Galiën, van der, O.; Gutteling, J.; Kraaij, W.; Veugen, T.
Enabling analytics on sensitive medical data with secure multi-party computation
published pages: , ISSN: , DOI:
STARTPAGE=76;ENDPAGE=80;TITLE=Building Continents of Knowledge in Oceans of Data: The Future of Co-Created eHealth 1 2020-03-06
2018 Jacob, Riko; Larsen, Kasper Green; Nielsen, Jesper Buus
Lower Bounds for Oblivious Data Structures
published pages: , ISSN: , DOI:
1 2020-03-06
2018 Brânzei, Simina; Orlandi, Claudio; Yang, Guang
Sharing Information with Competitors
published pages: , ISSN: , DOI:
1 2020-03-06
2017 Arnout Jaspers
Sharing Secrets (Without Giving Them Away)
published pages: , ISSN: , DOI:
2020-02-19
2017 Satrajit Ghosh (Aarhus University), Jesper Buus Nielsen (Aarhus University), Tobias Nilges (Aarhus University)
Maliciously Secure Oblivious Linear Function Evaluation with Constant Overhead
published pages: , ISSN: , DOI:
2020-02-19
2018 Ivan Damgård, Ji Lao, Sabine Oechsner, Mark Simkin, Peter Scholl
Compact Zero-Knowledge Proofs of Small Hamming Weight
published pages: , ISSN: , DOI:
2020-02-19
2018 Peter Scholl
Extending Oblivious Transfer with Low Communication via Key-Homomorphic PRFs
published pages: , ISSN: , DOI:
2020-02-19
2018 Ivan Damgård, Claudio Orlandi, Mark Simkin
Yet Another Compiler for Active Security or: Efficient MPC Over Arbitrary Rings
published pages: , ISSN: , DOI:
2020-02-19
2018 Tore Frederiksen, Benny Pinkas, Avishay Yanai
Committed MPC - Maliciously Secure Multiparty Computation from Homomorphic Commitments
published pages: , ISSN: , DOI:
2020-02-19
2017 Niek Bouman, Mykola Pechenizkiy
Data Mining with Secure Computation
published pages: , ISSN: , DOI:
2020-02-19
2017 Prastudy Fauzi (Aarhus University), Helger Lipmaa (University of Tartu), Janno Siim (University of Tartu and STACC), Michał Zając (University of Tartu)
An Efficient Pairing-Based Shuffle Argument
published pages: , ISSN: , DOI:
2020-02-19
2017 Meilof Veeningen
Distributed Privacy-Preserving Data Mining in the Medical Domain
published pages: , ISSN: , DOI:
2020-02-19
2018 Peter Scholl
Efficient MPC From Syndrome Decoding
published pages: , ISSN: , DOI:
2020-02-19
2018 Ronald Cramer, Ivan Damgård, Daniel Escudero, Peter Scholl, Chaoping Xing
SPDZ_2^k: Efficient MPC mod 2^k for Dishonest Majority
published pages: , ISSN: , DOI:
2020-02-19
2016 Milan Petkovic
SODA - Scalable Oblivious Data Analytics
published pages: , ISSN: , DOI:
2020-02-19
2017 Meilof Veeningen
SODA - Scalable Oblivious Data Analytics
published pages: , ISSN: , DOI:
2020-02-19
2018 Frank Blom, Niek Bouman, Berry Schoenmakers, Niels de Vreede
Secure Linear Algebra over F_p and Q
published pages: , ISSN: , DOI:
2020-02-19
2017 Meilof Veeningen
Pinocchio-Based Adaptive zk-SNARKs, Secure Adaptive Function Evaluation and Privacy-Preserving Medical Research
published pages: , ISSN: , DOI:
2020-02-19
2018 Carmit Hazay, Emmanuela Orsini, Peter Scholl , Eduardo Soria-Vazquez
TinyKeys: A New Approach to Efficient Multi-Party Computation
published pages: , ISSN: , DOI:
2020-02-19
2017 Carmit Hazay (Bar-Ilan University), Peter Scholl (Aarhus University), Eduardo Soria-Vazquez (University of Bristol)
Low Cost Constant Round MPC Combining BMR and Oblivious Transfer
published pages: , ISSN: , DOI:
2020-02-19
2017 Meilof Veeningen
Pinocchio-Based Adaptive zk-SNARKs and Secure/Correct Adaptive Function Evaluation
published pages: 21-39, ISSN: , DOI: 10.1007/978-3-319-57339-7_2
2020-02-19
2017 Jesper Buus Nielsen (Aarhus University) Thomas Schneider (Technische Universität Darmstadt) Roberto Trifiletti (Aarhus University)
Constant Round Maliciously Secure 2PC with Function-independent Preprocessing using LEGO
published pages: , ISSN: , DOI:
2020-02-19
2017 Helene Haagh, Yue Ji, Chenxing Li, Claudio Orlandi, and Yifan Song
Revealing Encryption for Partial Ordering
published pages: , ISSN: , DOI:
2020-02-19
2018 Meilof VEENINGEN, Supriyo CHATTERJEA, Anna Zsófia HORVÁTH, Gerald SPINDLERb, Eric BOERSMA, Peter van der SPEK, Onno van der GALIËN, Job GUTTELING, Wessel KRAAIJ, Thijs VEUGEN
Enabling Analytics on Sensitive Medical Data with Secure Multi-Party Computation
published pages: , ISSN: , DOI:
2020-02-19
2017 Meilof Veeningen
Philips, Big Data & healthcare
published pages: , ISSN: , DOI:
2020-02-19
2017 Meilof Veeningen
PySNARK
published pages: , ISSN: , DOI:
2020-02-19
2018 Meilof Veeningen
PySNARK announcement (flash presentation)
published pages: , ISSN: , DOI:
2020-02-19
2017 Peter Scholl (Aarhus University), Nigel Smart (University of Bristol), Tim Wood (University of Bristol)
When It’s All Just Too Much: Outsourcing MPC-Preprocessing
published pages: , ISSN: , DOI:
2020-02-19
65535 Martine De Cock, Rafael Dowsley, Caleb Horst, Raj Katti, Anderson Nascimento, Wing-Sea Poon, Stacey Truex
Efficient and Private Scoring of Decision Trees, Support Vector Machines and Logistic Regression Models based on Pre-Computation
published pages: 1-1, ISSN: 1545-5971, DOI: 10.1109/TDSC.2017.2679189
IEEE Transactions on Dependable and Secure Computing 2020-02-19
2017 Niek Bouman, Berry Schoenmakers
Introduction to Secure Multiparty Computation
published pages: , ISSN: , DOI:
2020-02-19
2017 Jesper Buus Nielsen, Samuel Ranellucci
On the Computational Overhead of MPC with Dishonest Majority
published pages: 369-395, ISSN: , DOI: 10.1007/978-3-662-54388-7_13
2020-02-19
2017 Arnout Jaspers
Geheimen delen met partners die je niet vertrouwt
published pages: , ISSN: , DOI:
2020-02-19
2018 Tore Frederiksen, Yehuda Lindell, Valery Osheter, Benny Pinkas
Fast Distributed RSA Key Generation for Semi-Honest and Malicious Adversaries
published pages: , ISSN: , DOI:
2020-02-19
2017 Nico Döttling, Satrajit Ghosh, Jesper Buus Nielsen, Tobias Nilges, Roberto Trifiletti
TinyOLE: Efficient Actively Secure Two-Party Computation from Oblivious Linear Function Evaluation
published pages: , ISSN: , DOI:
2020-02-19

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