Task Oriented Privacy (TOP) technologies

Abstract

One major shortcoming with most of the exiting privacy preserving techniques is that, they do not make any assumption about the ultimate usage of the data. Therefore, they follow a 'one-size-fits-all' strategy which usually results in an inefficient solution and consequently leads to over-anonymization and information loss. We propose a Task Oriented Privacy (TOP) model and its corresponding software system which incorporates the ultimate usage of the data into the privacy preserving data mining and data publishing process. Our model allows the data recipient to perform privacy preserving data mining including data pre-processing using metadata. It also provides an intelligent privacy preserving data publishing technique guided by feature selection and personalized privacy preferences. © 2014 Springer International Publishing.