A reproducible synthetic network traffic dataset with ground-truth anomaly labels, generated for benchmarking anomaly detection algorithms. Contains 19,643 log entries spanning 72 hours across a simul
This work intend to identify characteristics in network traffic that are able to distinguish the normal network behavior from denial of service attacks. One way to classify anomalous traffic is the da
The data is about the behaviors and activities of how participants use the CoRE system (http://core.cs.iastate.edu) and attack the system, such as clicking the buttons and links, filling out a form on
