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Secure Outsourced Data Analytics

Abstract : The goal of this document is to summarize my research activities since my recruitment as a Maître de Conférences in 2016. Most of my research in this period has been dedicated to addressing the data security concerns that occur when outsourcing some data to the cloud and then performing some computations (such as evaluating a query or a machine learning algorithm) on the data directly in the cloud. I focused on the honest-but-curious cloud model i.e., that executes tasks dutifully, but tries to gain as much information as possible. I contributed to: (i) secure evaluation of SPARQL queries on outsourced graphs, as well as synthetic generation of graphs and queries; (ii) secure protocols for sequential machine learning algorithms, with an emphasis on multi-armed bandits; (iii) secure MapReduce protocols for matrix multiplication and relational query evaluation. Our approach consists of developing distributed and secure protocols that combine existing algorithms with cryptographic schemes (such as AES and Paillier) and secure multi-party computations. Our protocols guarantee the same result as the standard, non-secure algorithms while enjoying desirable security properties.
Keywords : Data security
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https://tel.archives-ouvertes.fr/tel-03256882
Contributor : Radu Ciucanu Connect in order to contact the contributor
Submitted on : Thursday, June 10, 2021 - 3:02:58 PM
Last modification on : Thursday, December 16, 2021 - 9:22:02 AM
Long-term archiving on: : Saturday, September 11, 2021 - 7:12:12 PM

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  • HAL Id : tel-03256882, version 1

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Radu Ciucanu. Secure Outsourced Data Analytics. Databases [cs.DB]. Université d'Orléans, 2021. ⟨tel-03256882⟩

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