Semantic Security: Privacy Definitions Revisited
Jinfei Liu, Li Ping Xiong, Jun Luo · 2013
Abstract. In this paper ∗ we illustrate a privacy framework named Indistinguishable † Privacy. In-distinguishable privacy could be deemed as the formalization of the existing privacy definitions in privacy preserving data publishing as well as secure multi-party computation. We introduce three representative privacy notions in the literature, Bayes-optimal privacy for privacy preserving data publishing, differential privacy for statistical data release, and privacy w.r.t. semi-honest behavior in the secure multi-party computation setting, and prove they are equivalent. To the best of our knowl-edge, this is the first work that illustrates the relationships of these privacy definitions and unifies them through one framework.