K-anonymity privacy protection using ontology
Maede Ashouri-Talouki, Mohammad Ali Nematbakhsh, Ahmad Baraani-Dastjerdi · 2009 14th International CSI Computer Conference · 2009
Blinded data mining is a branch of data mining technique which is focused on protecting user privacy. To mine sensitive data such as medical information, it is desirable to protect privacy and there is not worry about revealing personalized data. In this paper a new approach for blinded data mining is suggested. It is based on ontology and k-anonymity generalization method. Our method generalizes a private table by considering table fields' ontology, so that each tuple will become k-anonymous and less specific to not reveal sensitive information. This method is implemented using protégé and java for evaluation.