In this paper, we address this challenge in enabling MLT-PPDM services. In particular, we focus on the additive perturbation approach where random Gaussian noise is added to the original data with arbitrary distribution, and provide a systematic solution. Through a one-to-one mapping, our solution allows a data owner to generate distinctly perturbed copies of its […]