CIC-IDS2017
A commonly used network intrusion detection dataset containing multiple attack scenarios and multi-day traffic. It is frequently used to evaluate model robustness under temporal drift.
Timeline (last 90 days)
On the three benchmarks UNSW-NB15, CIC-IDS2017, and EMBER2024, the paper compares against calibrated XGBoost, Random-Forest, MLP, and Kitsune, and measures a two-stage cascade of "Suricata (52,674 Emerging-Threats rules) → VX-One" running over five days on CIC-IDS2017.
VX-One wins on the detection metrics (AUROC, FPR@95%TPR) on UNSW-NB15, and also leads under the temporal drift conditions of CIC-IDS2017 (0.711 vs 0.637).
In the leave-one-family-out test, the VX-One gate successfully detected never-before-seen attack families on all 9 folds of UNSW (9/9), but on the CIC recon family its detection rate fell below random level.
All Facts (3)
On the three benchmarks UNSW-NB15, CIC-IDS2017, and EMBER2024, the paper compares against calibrated XGBoost, Random-Forest, MLP, and Kitsune, and measures a two-stage cascade of "Suricata (52,674 Emerging-Threats rules) → VX-One" running over five days on CIC-IDS2017.
50%UnverifiedVX-One wins on the detection metrics (AUROC, FPR@95%TPR) on UNSW-NB15, and also leads under the temporal drift conditions of CIC-IDS2017 (0.711 vs 0.637).
50%UnverifiedIn the leave-one-family-out test, the VX-One gate successfully detected never-before-seen attack families on all 9 folds of UNSW (9/9), but on the CIC recon family its detection rate fell below random level.
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