Measuring Anonymity with Relative Entropy Yuxin Deng, Jun Pang, and Peng Wu Anonymity is the property of maintaining secret the identity of users performing a certain action. Anonymity protocols often use random mechanisms which can be described probabilistically. In this paper, we propose a probabilistic process calculus to describe protocols for ensuring anonymity, and we use the notion of relative entropy from information theory to measure the degree of anonymity these protocols can guarantee. Furthermore, we prove that the operators in the probabilistic process calculus are non-expansive, with respect to this measuring method. We illustrate our approach by using the example of the Dining Cryptographers Problem.