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PCS: a parity-based personal data recovery service in cloud

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dc.contributor.authorJung, Hyungsoo-
dc.contributor.authorPark, Yongsu-
dc.contributor.authorSong, Chi-Won-
dc.contributor.authorKang, Sooyong-
dc.date.accessioned2022-07-13T12:02:18Z-
dc.date.available2022-07-13T12:02:18Z-
dc.date.created2021-05-12-
dc.date.issued2017-09-
dc.identifier.issn1386-7857-
dc.identifier.urihttps://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/151697-
dc.description.abstractAs more and more data are generated in an electronic format, the necessity of a data recovery service has increased, and the development of more efficient data backup and recovery technology has been an important issue during the past decade. While lots of effective backup and recovery technologies have been developed for enterprise level, little work has been done for convenient and inexpensive personal data recovery service, i.e., cloud storage service is still inadequate or expensive for backing up tera-scale HDDs. Furthermore, since privacy protection is a crucial issue for providing a personal data recovery service, a plain data backup-based recovery service is not adequate for public service. Users are reluctant to upload their data to internet backup servers until they can fully trust the service provider in terms of privacy protection. We propose a novel data recovery service framework on cloud infrastructure, a parity cloud service, which provides privacy-protected personal data recovery service while requiring a small storage space in the cloud. The proposed framework does not require any user data to be uploaded to the server, but only parity data are uploaded to the server for user data recovery. Also, the necessary server-side resources for providing the service are within a reasonable bound, depending on the data recover-ability and recovery time.-
dc.language영어-
dc.language.isoen-
dc.publisherSPRINGER-
dc.titlePCS: a parity-based personal data recovery service in cloud-
dc.typeArticle-
dc.contributor.affiliatedAuthorJung, Hyungsoo-
dc.contributor.affiliatedAuthorPark, Yongsu-
dc.contributor.affiliatedAuthorKang, Sooyong-
dc.identifier.doi10.1007/s10586-017-0805-8-
dc.identifier.scopusid2-s2.0-85014016724-
dc.identifier.wosid000407928800056-
dc.identifier.bibliographicCitationCLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS, v.20, no.3, pp.2655 - 2668-
dc.relation.isPartOfCLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS-
dc.citation.titleCLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS-
dc.citation.volume20-
dc.citation.number3-
dc.citation.startPage2655-
dc.citation.endPage2668-
dc.type.rimsART-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalWebOfScienceCategoryComputer Science, Information Systems-
dc.relation.journalWebOfScienceCategoryComputer Science, Theory & Methods-
dc.subject.keywordPlusDigital storage-
dc.subject.keywordPlusDistributed database systems-
dc.subject.keywordPlusRecovery-
dc.subject.keywordAuthorParity cloud service-
dc.subject.keywordAuthorPrivacy-
dc.subject.keywordAuthorBackup-
dc.subject.keywordAuthorParity-
dc.identifier.urlhttps://link.springer.com/article/10.1007/s10586-017-0805-8-
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