An Efficient Privacy Preserving Data Publishing Models for Relational Datasets

dc.contributor.guidePrakash, M
dc.coverage.spatial
dc.creator.researcherJayapradha, J
dc.date.accessioned2023-08-25T10:19:28Z
dc.date.available2023-08-25T10:19:28Z
dc.date.awarded2023
dc.date.completed2023
dc.date.registered
dc.description.abstractPrivacy is a significant issue that requires consideration in all applications. Data collected from various individuals and organizations must be disclosed to the public or private parties for analysis and research purposes. The collected data are studied and analyzed digitally for the extraction of various useful patterns for decision-making research purposes. Many privacy laws are available for the protection of information relating to individuals and organizations. However, the related laws differ from domain to domain. The data must be disclosed to the researchers despite the significant danger of leaking sensitive attributes to retrieve relevant information. Misinterpretation of personal data might have negative consequences also. The primary objective for disclosing the data is to use the individual s data for good reasons. The sensitive attribute in the datasets differs according to the applications newline
dc.description.note
dc.format.accompanyingmaterialDVD
dc.format.dimensions
dc.format.extent
dc.identifier.urihttp://hdl.handle.net/10603/508593
dc.languageEnglish
dc.publisher.institutionDepartment of Computer Science Engineering
dc.publisher.placeKattankulathur
dc.publisher.universitySRM Institute of Science and Technology
dc.relation
dc.rightsuniversity
dc.source.universityUniversity
dc.subject.keywordAutomation and Control Systems
dc.subject.keywordComputer Science
dc.subject.keywordEngineering and Technology
dc.titleAn Efficient Privacy Preserving Data Publishing Models for Relational Datasets
dc.title.alternative
dc.type.degreePh.D.

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