Abstrato

Studies on Protecting Privacy of Anonymized Medical Data

T.Kowshiga, T.Saranya, T.Jayasudha, Prof.M.Sowmiya and Prof.S.Balamurugan

This paper details about various methods prevailing in literature for protecting privacy of anonymized medical data. Ontology Based measure to compute semantic similarity in Biomedicine is studied. Ordinal, continuous and heterogeneous K-Anonymity through Microaggregation are dealt in detail. Protecting patient privacy by quantifiable control of disclosure in disseminated databases and achieving k-Anonymity privacy protection using generalization and suppression are discussed in detail. Efficient Multivariate data-Oriented Micro aggregation of Categorical data for confidential documents is examined. Differential Privacy for Automatic De-Identification of textual documents in the electronic health records and Statistical Disclosure control for patient records in biomedical information System is considered. Density-based microaggregation for statistical disclosure control and anonymization of Set-Valued Data via Top-Down, Local Generalization are also aggregated in brief. This paper would promote a lot of research in the area of protecting privacy of anonymized medical data.