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

Title: FRESQUE: A Scalable Ingestion Framework for Secure Range Query Processing on Clouds
Authors: van Tran, Hoang; Allard, Tristan; d'Orazio, Laurent; El Abbadi, Amr
Contributors: A Symbolic and Human-centric view of dAta MANagement (SHAMAN); GESTION DES DONNÉES ET DE LA CONNAISSANCE (IRISA-D7); Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA); Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes); Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique); Institut Mines-Télécom Paris (IMT)-Institut Mines-Télécom Paris (IMT)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes); Institut Mines-Télécom Paris (IMT)-Institut Mines-Télécom Paris (IMT)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA); Institut Mines-Télécom Paris (IMT)-Institut Mines-Télécom Paris (IMT); Can Tho University Vietnam (CTU); Declarative & Reliable management of Uncertain, user-generated Interlinked Data (DRUID); Security & PrIvaCY (SPICY); SYSTÈMES LARGE ÉCHELLE (IRISA-D1); Department of Computer Science Santa Barbara (CS-UCSB); University of California Santa Barbara (UC Santa Barbara); University of California (UC)-University of California (UC); This work was partially funded by LTC and Pôle d’Excellence Cyber
Source: EDBT 2021 - 24th International Conference on Extending Database Technology ; https://inria.hal.science/hal-03198346 ; EDBT 2021 - 24th International Conference on Extending Database Technology, Mar 2021, Nicosia, Cyprus. ⟨10.5441/002/edbt.2021.19⟩
Publisher Information: HAL CCSD
Publication Year: 2021
Collection: Université de Rennes 1: Publications scientifiques (HAL)
Subject Terms: [INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB]; [INFO.INFO-CR]Computer Science [cs]/Cryptography and Security [cs.CR]; [INFO.INFO-DC]Computer Science [cs]/Distributed; Parallel; and Cluster Computing [cs.DC]
Subject Geographic: Nicosia; Cyprus
Description: International audience ; 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.
Document Type: conference object
Language: English
DOI: 10.5441/002/edbt.2021.19
Availability: https://inria.hal.science/hal-03198346; https://inria.hal.science/hal-03198346/document; https://inria.hal.science/hal-03198346/file/p55.pdf; https://doi.org/10.5441/002/edbt.2021.19
Rights: info:eu-repo/semantics/OpenAccess
Accession Number: edsbas.70BDDC3
Database: BASE