CAD-CICUNSW is a single-source continual anomaly detection benchmark scenario for network intrusion detection. It is derived from CIC-UNSW-NB15 / UNSW-NB15 and converts the original tabular network-intrusion data into a sequence of concept-grouped tasks.
The dataset contains 1,084,928 samples, 5 tasks, and has a reported 12.76% anomaly ratio in the test set.
The dataset is anonymized for double-blind NeurIPS review. Author names, institutional… See the full description on the dataset page: https://huggingface.co/datasets/anonymizeddb/CAD-CICUNSW.
