Constructive Privacy for Shared Genetic Data

Fatima-Zahra Boujdad 1, 2 Mario Südholt 2
2 STACK - Software Stack for Massively Geo-Distributed Infrastructures
Inria Rennes – Bretagne Atlantique , LS2N - Laboratoire des Sciences du Numérique de Nantes
Abstract : The need for the sharing of genetic data, for instance, in genome-wide association studies is incessantly growing. In parallel, serious privacy concerns rise from a multi-party access to genetic information. Several techniques , such as encryption, have been proposed as solutions for the privacy-preserving sharing of genomes. However, existing programming means do not support guarantees for privacy properties and the performance optimization of genetic applications involving shared data. We propose two contributions in this context. First, we present new cloud-based architectures for cloud-based genetic applications that are motivated by the needs of geneticians. Second, we propose a model and implementation for the composition of watermarking with encryption, fragmentation, and client-side computations for the secure and privacy-preserving sharing of genetic data in the cloud.
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Communication dans un congrès
CLOSER 2018 - 8th International Conference on Cloud Computing and Services Science, Mar 2018, Funchal, Madeira, Portugal. pp.1-8, 2018, Proceedings of CLOSER 2018
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Soumis le : mardi 6 février 2018 - 19:34:03
Dernière modification le : jeudi 19 avril 2018 - 11:46:06

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Fatima-Zahra Boujdad, Mario Südholt. Constructive Privacy for Shared Genetic Data. CLOSER 2018 - 8th International Conference on Cloud Computing and Services Science, Mar 2018, Funchal, Madeira, Portugal. pp.1-8, 2018, Proceedings of CLOSER 2018. 〈hal-01692620v2〉

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