We describe the implementation of an approach for supporting secure query processing over sensors data in a multi-provider scenario. Our solution relies on the definition of authorizations regulating access to data according to three different visibility levels (no visibility, encrypted visibility, and plaintext visibility). Data processing is performed by multiple providers based on the restrictions imposed by authorizations, which may require to adjust data visibility on the fly. We describe the structure of the query optimizer and show how the operations of a computation can be assigned to different cloud providers to build an efficient, secure, and economical plan for collaborative data processing.

Multi-Provider Secure Processing of Sensors Data / E. Bacis, S. De Capitani di Vimercati, D. Facchinetti, S. Foresti, G. Livraga, S. Paraboschi, M. Rosa, P. Samarati - In: 2019 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops)[s.l] : IEEE, 2019 Jun. - ISBN 9781538691526. - pp. 349-351 (( Intervento presentato al 17. convegno International Conference on Pervasive Computing and Communications tenutosi a Kyoto nel 2019.

Multi-Provider Secure Processing of Sensors Data

S. De Capitani di Vimercati;S. Foresti;G. Livraga;P. Samarati
2019

Abstract

We describe the implementation of an approach for supporting secure query processing over sensors data in a multi-provider scenario. Our solution relies on the definition of authorizations regulating access to data according to three different visibility levels (no visibility, encrypted visibility, and plaintext visibility). Data processing is performed by multiple providers based on the restrictions imposed by authorizations, which may require to adjust data visibility on the fly. We describe the structure of the query optimizer and show how the operations of a computation can be assigned to different cloud providers to build an efficient, secure, and economical plan for collaborative data processing.
Settore INF/01 - Informatica
   Multi-Owner data Sharing for Analytics and Integration respecting Confidentiality and Owner control (MOSAICrOWN)
   MOSAICrOWN
   EUROPEAN COMMISSION
   H2020
   825333
giu-2019
IEEE
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/656625
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