Information Security Commons^™

An Iterative Association Rule Mining Framework To K-Anonymize A Dataset, Michael Hayes, Miriam A M Capretz, Jefferey Reed, Cheryl Forchuk

Electrical and Computer Engineering Publications

Preserving and maintaining client privacy and anonymity is of utmost importance in any domain and specially so in healthcare, as loss of either of these can result in legal and ethical implications. Further, it is sometimes important to extract meaningful and useful information from existing data for research or management purposes. In this case it is necessary for the organization who manages the dataset to be certain that no attributes can identify individuals or group of individuals. This paper proposes an extendable and generalized framework to anonymize a dataset using an iterative association rule mining approach. The proposed framework also …