Operating System (OS) virtualization, also known as container-based virtualization, has gained momentum over the past few years thanks to its lightweight nature and support for agility. However, its compelling features come at the price of a reduced isolation level compared to the traditional host-based virtualization techniques, exposing workloads to various threats, such as container escape. In those threats, compromised or rogue containers might exploit existing vulnerabilities or poor container deployment choices to successfully inject security state errors (e.g., breaking out of the namespace isolation mechanisms and running as a root at the host level). To effectively detect those security state errors, we would like to monitor containers at the system call level as the latter accurately maps processes to their activities. Hence, the objective of this project is firstly to study and compare existing monitoring tools (generic such as strace, or container-specific such as sysdig) and select the most suitable one according to a set of criteria (e.g., resource consumption, offered monitoring options). Secondly, the chosen monitoring tool will be instrumented for different scenarios (benign and anomalous settings) to generate relevant datasets capturing the behavior of containers with respect to a set of planned (malicious and benign) activities within a time window. The datasets will be subsequently vetted to extract critical system calls and execution paths that need to receive attention in the runtime detection process.