With the growing amount of personal information exchanged over the Internet,
privacy is becoming more and more a concern for users. One of the key
principles in protecting privacy is data minimisation. This principle requires
that only the minimum amount of information necessary to accomplish a certain
goal is collected and processed. "Privacy-enhancing" communication protocols
have been proposed to guarantee data minimisation in a wide range of
applications. However, currently there is no satisfactory way to assess and
compare the privacy they offer in a precise way: existing analyses are either
too informal and high-level, or specific for one particular system. In this
work, we propose a general formal framework to analyse and compare
communication protocols with respect to privacy by data minimisation. Privacy
requirements are formalised independent of a particular protocol in terms of
the knowledge of (coalitions of) actors in a three-layer model of personal
information. These requirements are then verified automatically for particular
protocols by computing this knowledge from a description of their
communication. We validate our framework in an identity management (IdM) case
study. As IdM systems are used more and more to satisfy the increasing need for
reliable on-line identification and authentication, privacy is becoming an
increasingly critical issue. We use our framework to analyse and compare four
identity management systems. Finally, we discuss the completeness and
(re)usability of the proposed framework