Monitoring of host-based events and network flows are the two most common techniques for collecting and analyzing cybersecurity data. However, events and flows are either monitored separately or correlated as alerts in higher aggregated forms. The event-flow correlation on the monitoring level would match related events and flows together and enabled observing both data in near real-time. This approach allows substituting application-level flow information that will not be available due to encryption, which is being employed in a number of communication protocols. In this paper, we performed the event-flow correlation of the DNS protocol. We developed a general model that describes the relation between events and flows to enable an accurate time-based correlation where parameter-based correlation is not feasible. Based on the model, we designed three event-flow correlation methods based on common parameters and times of occurrence. We evaluated the correlation methods using a recent and public dataset, both with and without the extended flow information, to simulate DNS flow encryption. The results of the method combining parameter-based and time-based matching show that matching related DNS events to flows is possible and substitutes the data that might soon be lost in encryption.