Probability comprehension of differential privacy for privacy protection algorithms: A new measure

摘要

Differential privacy becomes a standard for evaluating the privacy protection performance for an algorithm these years. However, the definition of differential privacy seems not so easy to understand as the classical k-anonymity and etc. In this paper, we propose a new measure which is more comprehensible. Some properties of such measure are investigated and the relationship between our new definition and differential privacy is studied.