Injecting purpose and trust into data anonymisation

Abstract

Most existing works of data anonymisation target at the optimization of the anonymisation metrics to balance the data utility and privacy, whereas they ignore the effects of a requester's trust level and application purposes during the data anonymisation. Our aim of this paper is to propose a much finer level anonymisation scheme with regard to the data requester's trust value and specific application purpose. We prioritize the attributes for anonymisation based on how important and critical they are related to the specified application purposes and propose a trust evaluation strategy to quantify the data requester's reliability, and further build the projection between the trust value and the degree of data anonymiztion, which intends to determine to what extent the data should be anonymized. The decomposition algorithm is developed to find the desired anonymous solution, which guarantees the uniqueness and correctness.