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Privacy Preserving Multi Party Computation for Data-Analytics in the IoT-Fog-Cloud Ecosystem

Abstract : In this paper, we propose an architecture for privacy pre- serving protocols in an IoT-Fog-Cloud ecosystem computing hierarchy. We consider the paradigms of Fog and Edge computing, together with a multi-party computation mechanism that enables secure privacy-preserving data processing in terms of exchanged messages and distributed comput- ing. We discuss the potential use of such an architecture in a scenario of pandemics where social distancing monitoring and privacy are pivotal to manage public health yet providing confidence to citizens.
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https://hal.inria.fr/hal-03142821
Contributor : Nikolaos Georgantas Connect in order to contact the contributor
Submitted on : Tuesday, February 16, 2021 - 12:22:56 PM
Last modification on : Friday, August 5, 2022 - 11:41:03 AM
Long-term archiving on: : Monday, May 17, 2021 - 7:07:15 PM

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  • HAL Id : hal-03142821, version 1

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Julio Lopez-Fenner, Samuel Sepulveda, Luiz Fernando Bittencourt, Fabio Moreira Costa, Nikolaos Georgantas. Privacy Preserving Multi Party Computation for Data-Analytics in the IoT-Fog-Cloud Ecosystem. CICCSI 2020 : IV International Congress of Computer Sciences and Information Systems, Nov 2020, Mendoza / Virtual, Argentina. ⟨hal-03142821⟩

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