survey

Ensuring Security and Privacy Preservation for Cloud Data Services

Authors:

Jiangchuan Liu,

Rajkumar BuyyaAuthors Info & Claims

ACM Computing Surveys (CSUR), Volume 49, Issue 1

Article No.: 13, Pages 1 - 39

https://doi.org/10.1145/2906153

Published: 06 June 2016 Publication History

Abstract

With the rapid development of cloud computing, more and more enterprises/individuals are starting to outsource local data to the cloud servers. However, under open networks and not fully trusted cloud environments, they face enormous security and privacy risks (e.g., data leakage or disclosure, data corruption or loss, and user privacy breach) when outsourcing their data to a public cloud or using their outsourced data. Recently, several studies were conducted to address these risks, and a series of solutions were proposed to enable data and privacy protection in untrusted cloud environments. To fully understand the advances and discover the research trends of this area, this survey summarizes and analyzes the state-of-the-art protection technologies. We first present security threats and requirements of an outsourcing data service to a cloud, and follow that with a high-level overview of the corresponding security technologies. We then dwell on existing protection solutions to achieve secure, dependable, and privacy-assured cloud data services including data search, data computation, data sharing, data storage, and data access. Finally, we propose open challenges and potential research directions in each category of solutions.

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Ensuring Security and Privacy Preservation for Cloud Data Services

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cover image ACM Computing Surveys

ACM Computing Surveys Volume 49, Issue 1

March 2017

705 pages

ISSN:0360-0300

EISSN:1557-7341

DOI:10.1145/2911992

Editor:
Sartaj Sahni
Department of Computer and Information Science and Engineering/University of Florida/Gainesville, FL

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Copyright © 2016 ACM.

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Publication History

Published: 06 June 2016

Accepted: 01 March 2016

Revised: 01 January 2016

Received: 01 July 2015

Published in CSUR Volume 49, Issue 1

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Urvashi Bansal S(2025)Stochastic modeling and performance optimization of the cloud computing space system utilizing Petri nets simulation modeling and genetic algorithmInternational Journal of System Assurance Engineering and Management10.1007/s13198-024-02695-zOnline publication date: 8-Jan-2025
https://doi.org/10.1007/s13198-024-02695-z
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https://doi.org/10.48175/IJARSCT-18468
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