Our paper „Contextualizing System Calls in Containers for Anomaly-Based Intrusion Detection” got accepted at ACM CCSW 2022! In the paper, we describe a novel approach for anomaly-based intrusion detection tailored to running containers (in the sense of OS-level virtualization). Concretely, the approach is based on the training of an auto-encoder neural network, which primarily uses three features in a efficient graph representation: previously unseen system calls, previously unseen arguments of system calls, and the frequency of system calls. We can show that our approach is more effective and more efficient than existing approaches.