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Effective and efficient skyline query processing over attribute-order-preserving-free encrypted data in cloud-enabled databases

Authors :
Panagiotis Karras
Akrivi Vlachou
Alfredo Cuzzocrea
Istituto di Calcolo e Reti ad Alte Prestazioni [Rende] (ICAR-CNR)
Consiglio Nazionale delle Ricerche [Roma] (CNR)
Department of Algorithms, Computation, Image and Geometry (LORIA - ALGO)
Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA)
Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)
Catholic University of Leuven - Katholieke Universiteit Leuven (KU Leuven)
Athens University of Economics and Business (AUEB)
DIGITRUST
ANR-15-IDEX-0004,LUE,Isite LUE(2015)
National Research Council of Italy | Consiglio Nazionale delle Ricerche (CNR)
Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)
Source :
Future Generation Computer Systems, Future Generation Computer Systems, Elsevier, 2022, 126, pp.237-251. ⟨10.1016/j.future.2021.08.008⟩, Future Generation Computer Systems, 2022, 126, pp.237-251. ⟨10.1016/j.future.2021.08.008⟩, Cuzzocrea, A, Karras, P & Vlachou, A 2022, ' Effective and efficient skyline query processing over attribute-order-preserving-free encrypted data in cloud-enabled databases ', Future Generation Computer Systems, vol. 126, pp. 237-251 . https://doi.org/10.1016/j.future.2021.08.008
Publication Year :
2022
Publisher :
HAL CCSD, 2022.

Abstract

Making co-existent and convergent the need for efficiency of relational query processing over Clouds and the security of data themselves is figuring-out how one of the most challenging research problems in the Big Data era. Indeed, in actual analytics-oriented engines, such as Google Analytics and Amazon S3, where key–value storage-representation and efficient-management models are employed as to cope with the simultaneous processing of billions of transactions, querying encrypted data is becoming one of the most annoying problem, which has also attracted a great deal of attention from the research community. While this issue has been applied to a large variety of data formats, e.g. relational, RDF and multidimensional data, very few initiatives have pointed-out skyline query processing over encrypted data, which is, indeed, relevant for database analytics. In order to fulfill this methodological and technological gap, in this paper we introduce an innovative algorithm for effectively and efficiently supporting skyline query processing over encrypted data in Cloud-enabled databases, named as Attribute-Order-Preserving-Free-SFS ( AOPF-SFS ), a suitable extension of the well-known Sort-Filter-Skyline ( SFS ) algorithm. The proposed algorithm enables the processing of skyline queries over encrypted data, even without preserving the order on each attribute as order-preserving encryption would do. We also present eSkyline, a prototype system that embeds AOPF-SFS equipped with a suitable query interface comprising an encryption scheme that facilitates the evaluation of domination relationships, hence allows for state-of-the-art skyline processing algorithms to be used. In order to prove the effectiveness and the reliability of our system, we also provide the details of the underlying encryption scheme, plus a suitable GUI that allows a user to interact with a server, and showcases the efficiency of computing skyline queries and decrypting the results.

Details

Language :
English
ISSN :
0167739X
Database :
OpenAIRE
Journal :
Future Generation Computer Systems, Future Generation Computer Systems, Elsevier, 2022, 126, pp.237-251. ⟨10.1016/j.future.2021.08.008⟩, Future Generation Computer Systems, 2022, 126, pp.237-251. ⟨10.1016/j.future.2021.08.008⟩, Cuzzocrea, A, Karras, P & Vlachou, A 2022, ' Effective and efficient skyline query processing over attribute-order-preserving-free encrypted data in cloud-enabled databases ', Future Generation Computer Systems, vol. 126, pp. 237-251 . https://doi.org/10.1016/j.future.2021.08.008
Accession number :
edsair.doi.dedup.....47b7fb5aedb7c81d27e7829c8feec9c8
Full Text :
https://doi.org/10.1016/j.future.2021.08.008⟩