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Secure Joins with MapReduce

Abstract : MapReduce is one of the most popular programming paradigms that allows a user to process Big data sets. Our goal is to add privacy guarantees to the two standard algorithms of join computation for MapReduce: the cascade algorithm and the hypercube algorithm. We assume that the data is externalized in an honest-but-curious server and a user is allowed to query the join result. We design, implement, and prove the security of two approaches: (i) Secure-Private, assuming that the public cloud and the user do not collude, (ii) Collision-Resistant-Secure-Private, which resists to collusions between the public cloud and the user i.e., when the public cloud knows the secret key of the user.
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Contributor : Radu Ciucanu Connect in order to contact the contributor
Submitted on : Sunday, December 16, 2018 - 11:55:21 PM
Last modification on : Tuesday, January 4, 2022 - 5:22:28 AM
Long-term archiving on: : Sunday, March 17, 2019 - 1:11:11 PM


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  • HAL Id : hal-01903098, version 1


Xavier Bultel, Radu Ciucanu, Matthieu Giraud, Pascal Lafourcade, Lihua Ye. Secure Joins with MapReduce. FPS 2018 : The 11th International Symposium on Foundations & Practice of Security, Nov 2018, Montreal, Canada. ⟨hal-01903098⟩



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