Load balancing for privacy-preserving access to big data in cloud

Peng Li, Song Guo

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

8 Citations (Scopus)

Abstract

In the era of big data, many users and companies start to move their data to cloud storage to simplify data management and reduce data maintenance cost. However, security and privacy issues become major concerns because third-party cloud service providers are not always trusty. Although data contents can be protected by encryption, the access patterns that contain important information are still exposed to clouds or malicious attackers. In this paper, we apply the ORAM algorithm to enable privacy-preserving access to big data that are deployed in distributed file systems built upon hundreds or thousands of servers in a single or multiple geo-distributed cloud sites. Since the ORAM algorithm would lead to serious access load unbalance among storage servers, we study a data placement problem to achieve a load balanced storage system with improved availability and responsiveness. Due to the NP-hardness of this problem, we propose a low-complexity algorithm that can deal with large-scale problem size with respect to big data. Extensive simulations are conducted to show that our proposed algorithm finds results close to the optimal solution, and significantly outperforms a random data placement algorithm.
Original languageEnglish
Title of host publication2014 IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2014
PublisherIEEE
Pages524-528
Number of pages5
ISBN (Print)9781479930883
DOIs
Publication statusPublished - 1 Jan 2014
Externally publishedYes
Event2014 IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2014 - Toronto, ON, Canada
Duration: 27 Apr 20142 May 2014

Conference

Conference2014 IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2014
Country/TerritoryCanada
CityToronto, ON
Period27/04/142/05/14

ASJC Scopus subject areas

  • Computer Science(all)
  • Electrical and Electronic Engineering

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