A Large Dataset Enhanced Watermarking Service for Cloud Environments

dc.AffiliationOctober University for modern sciences and Arts (MSA)
dc.contributor.authorZawawi, Nour
dc.contributor.authorHamdy, Mohamed
dc.contributor.authorEl-Gohary, Rania
dc.contributor.authorFahmy Tolba, Mohamed
dc.date.accessioned2019-10-26T16:20:29Z
dc.date.available2019-10-26T16:20:29Z
dc.date.issued11/28/2014
dc.descriptionMSA Google Scholar
dc.description.abstractPreventing data abuses in cloud remains an essential point of the research. Proving the integrity and non-repudiation for large datasets over the cloud has an increasing attention of database community. Having security services based on watermarking techniques that enable permanent preservation for data tuples in terms of integrity and recovery for cloud environments presents the milestone of establishing trust between the data owners and the database cloud services. In this paper, an enhanced secure database service for Cloud environments (EWRDN) is proposed. It based over enhancements on WRDN as a data watermarking approach. The proposed service guarantees data integrity, privacy, and non-repudiation recovering data to its origin. Moreover, it gives data owner more controlling capabilities for their data by enabling tracing users’ activities. Two compression categories to recover data to its origin introduced for the proposed service. Two compression technique (the arithmetic encoding and the transform encoding) chosen to represent each type. For large data sets, it has been proven that, the arithmetic encoding has a fixed recovery ratio equal to one. At the same time, the transform encoding saves space and consumed less time to recover data. Moreover, testing the performance is done of the proposed service versus a large number of tuples, large data set. The performance quantified in terms of processing time and the required memory resources. The enhanced EWRDN service has shown a good performance in our experiments.en_US
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dc.identifier.doihttps://doi.org/10.1007/978-3-319-13461-1_10
dc.identifier.otherhttps://doi.org/10.1007/978-3-319-13461-1_10
dc.identifier.urihttps://cutt.ly/TyTKlxb
dc.language.isoen_USen_US
dc.publisherSpringer, Chamen_US
dc.relation.ispartofseriesInternational Conference on Advanced Machine Learning Technologies and Applications;P 87-96
dc.subjectCopyright protectionen_US
dc.subjectDigital Watermarkingen_US
dc.subjectSecurity Serviceen_US
dc.subjectData Compressionen_US
dc.subjectLarge dataseten_US
dc.titleA Large Dataset Enhanced Watermarking Service for Cloud Environmentsen_US
dc.typeArticleen_US

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