A Novel Method for Privacy Preserving Data Publishing
I G. Sivaranjani, G. Suganthi · 2014
There are many different reasons that people put forward to support the proposition that privacy is important. People need private space and need to be free to behave in public data sharing. Privacy protection is the interests of one person or category of people. Collaborative data publishing is a method which is used to share some helpful information like blood donor details in hospital. Collaborative data publishing may face various attacks like potential loss of integrated data utility. This work proposes a solution to one such attack called insider attack. m-privacy guarantees that the anonymized data satisfies a given privacy constraint. to solve the attacks provider- aware anonymization, high dimensional top down specialization algorithms are used. Provider aware anonymization algorithm is ensuring m-privacy methodology which is highest rated anonymized data with efficiency. Then, trusted third party would give anonymized data's to n-providers. High dimensional top down specialization achieves privacy.