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RETRACTED: Query processing over secure perturbed data over hybrid cloud

Sridhar Reddy Vulapula (Koneru Lakshmaiah Education Foundation, Guntur, India)
Srinivas Malladi (Koneru Lakshmaiah Education Foundation, Guntur, India)

International Journal of Intelligent Unmanned Systems

ISSN: 2049-6427

Article publication date: 28 December 2020

Issue publication date: 7 January 2022

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This article was retracted on 11 Jun 2024.

Retraction notice

The publishers of the International Journal of Intelligent Unmanned Systems wish to retract the article; Vulapula, S.R. and Malladi, S. (2022), “Query processing over secure perturbed data over hybrid cloud”, International Journal of Intelligent Unmanned Systems, Vol. 10 No. 1, pp. 22-33. https://doi.org/10.1108/IJIUS-09-2020-0054

An internal investigation into a series of submissions has uncovered evidence that the peer review process was compromised. As a result of these concerns, the findings of the article cannot be relied upon. This decision has been taken in accordance with Emerald’s publishing ethics and the COPE guidelines on retractions.

The authors of this paper would like to note that they do not agree with the content of this notice.

The publishers of the journal sincerely apologize to the readers

Abstract

Purpose

Hybrid cloud composing of public and private cloud is seen as a solution for storage of health care data characterized by many private and sensitive data. In many hybrid cloud-based solutions, the data are perturbed and kept in public cloud, and the perturbation credentials are kept in private cloud.

Design/methodology/approach

Hybrid cloud is a model combing private and public cloud. Security for the data is enforced using this distribution in hybrid clouds. However, these mechanisms are not efficient for range query and retrieval of data from cloud. In this work, a secure and efficient retrieval solution combining K-mean clustering, geometric perturbation and R-Tree indexing is proposed for hybrid clouds.

Findings

Compared to existing solution, the proposed indexing on perturbed data is able to achieve 33% reduced retrieval time. The security of indexes as measured using variance of differences was 66% more than existing solutions.

Originality/value

This study is an attempt for efficient retrieval of data with range queries using R-Tree indexing approach.

Keywords

Citation

Vulapula, S.R. and Malladi, S. (2022), "RETRACTED: Query processing over secure perturbed data over hybrid cloud", International Journal of Intelligent Unmanned Systems, Vol. 10 No. 1, pp. 22-33. https://doi.org/10.1108/IJIUS-09-2020-0054

Publisher

:

Emerald Publishing Limited

Copyright © 2020, Emerald Publishing Limited

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