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K-AMSOA: Privacy-Preserving Technique for Multiple Co-Related Sensitive Numeric Attributes using Dynamic Data Set

Nidhi M Chourey, Bhakti M.Thombre

Privacy Preservation of released data is a serious issue now days. If a dataset contains multiple correlated attributes then privacy concerns related to data set increases, because data publisher has to release data set in such a way that data is secure from disclosures as well as their co-relation is maintain as well. If attributes whose co-relations should be maintained contain set of multiple numerical sensitive attributes then the privacy preserving become very tough task. So, there is a need of a new privacy preservation technique which is specially focused on this direction. This work is focused on privacy preservation for dynamic dataset. Here, dynamic data set means data publisher can add or remove attributes at the time of applying privacy preservation technique and release results. Data set attributes may be vary as per dataset release objective.