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dc.contributor.authorChoi, Uinam Jung,en_US
dc.date.accessioned2013-08-16T12:28:53Z
dc.date.available2013-08-16T12:28:53Z
dc.date.issued1983en_US
dc.identifier.urihttps://hdl.handle.net/11244/5110
dc.description.abstractAn efficient and effective data distortion technique is introduced. This "Probability Data Distortion, " which is not easily compromisable and has asymptotically the same statistical properties as the original data, is significantly different from the conventional Point Data Distortion technique which adds random errors to the original values. This mechanism, the data distortion by probability distribution, is resistant to compromise and provides better exposure for statistical analysis than do the existing data distortion techniques.en_US
dc.description.abstractThe legal code on "The Protection of Human Subjects in Research Activities" requires that sensitive information about an individual should be protected from unauthorized release and at the same time, those data should be available for statistical analysis. To meet these conflicting goals, recent research efforts focus on creating distorted data which is not easily compromisable and yet preserves the statistical properties of the original data.en_US
dc.format.extentviii, 104 leaves :en_US
dc.subjectComputer Science.en_US
dc.titleInference control in statistical databases :en_US
dc.typeThesisen_US
dc.thesis.degreePh.D.en_US
dc.thesis.degreeDisciplineSchool of Electrical and Computer Engineeringen_US
dc.noteSource: Dissertation Abstracts International, Volume: 44-02, Section: B, page: 0543.en_US
ou.identifier(UMI)AAI8314760en_US
ou.groupCollege of Engineering::School of Electrical and Computer Engineering


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