  Process mining employs event logs to provide insights into the actual
processes. Event logs are recorded by information systems and contain valuable
information helping organizations to improve their processes. However, these
data also include highly sensitive private information which is a major concern
when applying process mining. Therefore, privacy preservation in process mining
is growing in importance, and new techniques are being introduced. The
effectiveness of the proposed privacy preservation techniques needs to be
evaluated. It is important to measure both sensitive data protection and data
utility preservation. In this paper, we propose an approach to quantify the
effectiveness of privacy preservation techniques. We introduce two measures for
quantifying disclosure risks to evaluate the sensitive data protection aspect.
Moreover, a measure is proposed to quantify data utility preservation for the
main process mining activities. The proposed measures have been tested using
various real-life event logs.
