The availability of a multitude of data sources has naturally increased the need for subjects to collaborate for distributed computations, aimed at combining different data collections for their elaboration and analysis. Due to the quick pace at which collected data grow, often the authorities collecting and owning such datasets resort to external third parties (e.g., cloud providers) for their storage and management. Data under the control of different authorities are autonomously encrypted (using a different encryption scheme and key) for their external storage. This makes distributed computations combining these sources hard. In this paper, we propose an approach enabling collaborative computations over data encrypted in storage, selectively involving also subjects that might not be authorized for accessing the data in plaintext when it is considered economically convenient.

Distributed query evaluation over encrypted data / S. De Capitani di Vimercati, S. Foresti, S. Jajodia, G. Livraga, S. Paraboschi, P. Samarati (LECTURE NOTES IN COMPUTER SCIENCE). - In: Data and Applications Security and Privacy XXXV / [a cura di] K. Barker, K. Ghazinour. - [s.l] : Springer Nature, 2021. - ISBN 9783030812416. - pp. 96-114 (( Intervento presentato al 35. convegno 35th Annual IFIP WG 11.3 Conference, DBSec 2021 tenutosi a Calgary nel 2021 [10.1007/978-3-030-81242-3_6].

Distributed query evaluation over encrypted data

S. De Capitani di Vimercati;S. Foresti;G. Livraga
;
P. Samarati
2021

Abstract

The availability of a multitude of data sources has naturally increased the need for subjects to collaborate for distributed computations, aimed at combining different data collections for their elaboration and analysis. Due to the quick pace at which collected data grow, often the authorities collecting and owning such datasets resort to external third parties (e.g., cloud providers) for their storage and management. Data under the control of different authorities are autonomously encrypted (using a different encryption scheme and key) for their external storage. This makes distributed computations combining these sources hard. In this paper, we propose an approach enabling collaborative computations over data encrypted in storage, selectively involving also subjects that might not be authorized for accessing the data in plaintext when it is considered economically convenient.
Settore INF/01 - Informatica
Multi-Owner data Sharing for Analytics and Integration respecting Confidentiality and Owner control (MOSAICrOWN)
Machine Learning-based, Networking and Computing Infrastructure Resource Management of 5G and beyond Intelligent Networks (MARSAL)
PRIN201719SDECA_01 - High quality Open data Publishing and Enrichment (HOPE) - DE CAPITANI DI VIMERCATI, SABRINA - PRIN2017 - PRIN bando 2017 - 2019
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/857614
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