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dc.contributor.authorChen, Yen-Chungen_US
dc.contributor.authorWu, Yu-Sungen_US
dc.contributor.authorTzeng, Wen-Gueyen_US
dc.date.accessioned2018-08-21T05:53:28Z-
dc.date.available2018-08-21T05:53:28Z-
dc.date.issued2018-03-01en_US
dc.identifier.issn1016-2364en_US
dc.identifier.urihttp://dx.doi.org/10.6688/JISE.2018.34.2.6en_US
dc.identifier.urihttp://hdl.handle.net/11536/144736-
dc.description.abstractWith the growth in the popularity of cloud storage service (CSS), the accumulation of private data on the cloud requires the use of data encryption to prevent leakage of sensitive information to untrusted third parties. However, as the amount of data kept on the cloud storage is increasing, the use of data encryption makes it difficult or even impossible to locate the data of interest efficiently and securely. In this paper, we present a framework for CSS to support queries in encrypted form so that the data on cloud storage can be located efficiently and securely. At the core of the framework is a novel indexing structure, called the bloom filter encrypted search tree (BFEST). The BFEST supports queries in the form of phrase keywords. Client-side encryption, using secret keys that are unknown to the cloud service provider, protects the queries and the retrieved data. We implemented a prototype by extending the hicloud S3 [13] CSS with the proposed framework. The experimental results indicate that the framework can ensure query privacy for encrypted data with an acceptable performance overhead in a practical setting.en_US
dc.language.isoen_USen_US
dc.subjectcloud storageen_US
dc.subjectprivacyen_US
dc.subjectencrypted searchen_US
dc.subjectphrase searchen_US
dc.subjectbloom filteren_US
dc.titlePhrase Search for Encrypted Cloud Storageen_US
dc.typeArticleen_US
dc.identifier.doi10.6688/JISE.2018.34.2.6en_US
dc.identifier.journalJOURNAL OF INFORMATION SCIENCE AND ENGINEERINGen_US
dc.citation.volume34en_US
dc.citation.spage401en_US
dc.citation.epage417en_US
dc.contributor.department資訊工程學系zh_TW
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.identifier.wosnumberWOS:000428362800006en_US
Appears in Collections:Articles