Latest News

Last 5th of December, PAPAYA Project was presented by Aljosa Pasic, director of Technology Transfer in Atos Research and Innovation Spain, at the round table of Aegis Cyber Event in Vienna. 

The second consortium meeting of the PAPAYA project took place on November 7-8, 2018 in Haifa (Israel) in the premises of IBM Israel. It coincided with the project’s 6 months of existence and brought together the six partners of PAPAYA.

Alberto Crespo, Head of Atos Privacy Lab, has represented PAPAYA project at the session "From Data Protection and Privacy to Fairness and Trust: the way forward" at EBDVF 2018, held in the Siemens Conference Center in Vienna.

We have promoted the PAPAYA project at the ISSE conference 2018, the well-known Trust & Security conference organized by EEMA.

PAPAYA project was presented at Smau in Milano, Italy last 23th of October.

Melek Önen, EURECOM associate professor in the Digital Security Department and PAPAYA Coordinator, gave an overview about the project at the event organized by the EU-funded H2020 project PoseID-on at the Italian Ministry of Economy and Finance (coordinator of PoseID-on) , Rome.

On September 7, 2018, Alberto Ibarrondo (EURECOM) presented the paper FHE-compatible Batch Normalization for Privacy Preserving Deep Learning at the 13th Data Privacy Management International Workshop (DPM 2018) in Barcelona, Spain, during the session Privacy and Cryptography.

Objectives

Multi-Setting Data Processing Protocols

There are several use cases intended to cover a realistic and wide variety of scenarios, where data flows interact with diverse sources and/or destinations. These collaborative analytics require a thoughtful analysis about the actors involved in terms of data protection and privacy, in order to conform to existing General Data Protection Regulation (GDPR).

Efficient Privacy-Preserving Big Data Analytics

The PAPAYA project provides tools that enable computation over a wide range of operations, from simple statistics to sophisticated machine learning algorithms, in a most efficient manner and while attaining functional requirements of a set of realistic scenarios we propose to validate the platform against.

Integrated Big Data Analytics Platform

PAPAYA´s final technical goal is to define a common framework for privacy-preserving Big Data Analytics that shows the relationship among privacy, protocols and analytics in each of the settings described and that fits into the each of the use cases. Besides, the platform should provide usable, user-friendly and accesible safeguard options.

Risk Management and User-Centric Dashboard

The PAPAYA platform will offer default, privacy-friendly configurations to users in order to enable a flexible trade-off between privacy and utility in Big Data Analytics, thus reducing the risk of data leakage. PAPAYA provides a dashboard which enables visualization to the data protection and privacy provisioned. Consequently this transparency increases trust in Big Data providers for Data Analytics while complying with existing regulations that focus on end-users' data protection and privacy.
 

End-to-End Use Case Validation

Two different use cases are proposed, healthcare and web analytics. The goal here is to derive functional and non-functional requirements that conform to the needs of the data analytics in question. These requirements evolve together with the design and implementation of the PAPAYA platform. This is also useful to ensure final validation of the platform according to the mentioned use cases.

Dissemination and Exploitation

The consortium will exploit the project results in the relevant communities, sectors (industrial, academic). Innovation and knowledge transfer activites are also contemplated in order to reach data analytics groups and stakeholders of interest.