Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/508593
Title: An Efficient Privacy Preserving Data Publishing Models for Relational Datasets
Researcher: Jayapradha, J
Guide(s): Prakash, M
Keywords: Automation and Control Systems
Computer Science
Engineering and Technology
University: SRM Institute of Science and Technology
Completed Date: 2023
Abstract: Privacy 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
Pagination: 
URI: http://hdl.handle.net/10603/508593
Appears in Departments:Department of Computer Science Engineering

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01_title.pdfAttached File173.73 kBAdobe PDFView/Open
02_preliminary page.pdf.pdf593.42 kBAdobe PDFView/Open
03_content.pdf592.33 kBAdobe PDFView/Open
04_abstract.pdf275.81 kBAdobe PDFView/Open
05_chapter 1.pdf1.32 MBAdobe PDFView/Open
06_chapter 2.pdf629.34 kBAdobe PDFView/Open
07_chapter 3.pdf1.8 MBAdobe PDFView/Open
08_chapter 4.pdf1.61 MBAdobe PDFView/Open
09_chapter 5.pdf1.72 MBAdobe PDFView/Open
10_chapter 6.pdf345.1 kBAdobe PDFView/Open
11_annexures.pdf369.3 kBAdobe PDFView/Open
80_recommendation.pdf385.1 kBAdobe PDFView/Open
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