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.

(2021). Distributed Query Evaluation over Encrypted Data . Retrieved from http://hdl.handle.net/10446/202632

Distributed Query Evaluation over Encrypted Data

Paraboschi, Stefano;
2021-01-01

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.
2021
De Capitani di Vimercati, Sabrina; Foresti, Sara; Jajodia, Sushil; Livraga, Giovanni; Paraboschi, Stefano; Samarati, Pierangela
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10446/202632
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