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FRESQUE: A Scalable Ingestion Framework for Secure Range Query Processing on Clouds

Abstract : Performing non-aggregate range queries over encrypted data stored on untrusted clouds has been considered by a large body of work over the last years. However, prior schemes mainly concentrate on improving query performance while the scalability dimension still remains challenging. Due to heavily pre-processing incoming data at a trusted component such as encrypting data and building secure indexes, existing solutions cannot provide a satisfactory ingestion throughput. In this paper, we overcome this limitation by introducing a framework for secure range query processing, FRESQUE, that enables a scalable consumption throughput while still maintaining strong privacy protection for outsourced data. Our experiments on real-world datasets show that FRESQUE can support over 160 thousand record insertions in a second, when running on a 12-computing node cluster. It also significantly outperforms one of the most efficient schemes such as PINED-RQ++ by 43 times on ingestion throughput.
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https://hal.inria.fr/hal-03198346
Contributor : Tristan Allard <>
Submitted on : Wednesday, April 14, 2021 - 5:28:05 PM
Last modification on : Friday, April 16, 2021 - 1:42:15 PM

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Hoang van Tran, Tristan Allard, Laurent d'Orazio, Amr El Abbadi. FRESQUE: A Scalable Ingestion Framework for Secure Range Query Processing on Clouds. EDBT 2021 - 24th International Conference on Extending Database Technology, Mar 2021, Nicosia, Cyprus. ⟨10.5441/002/edbt.2021.19⟩. ⟨hal-03198346⟩

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