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CICIDS

Benchmarks

Task NameDataset NameSOTA ResultTrend
Multi-class Network Intrusion DetectionCICIDS 2017
Accuracy98.6
39
Binary classificationCICIDS 2017
Binary Accuracy99.2
30
Binary classificationCICIDS 2017 (test)
F1-Score96.09
25
Anomaly DetectionCICIDS2017
After-Attack Accuracy85.99
24
Network Traffic ClassificationCICIDS i.i.d. settings 2017
Accuracy99.97
18
Time-series Anomaly DetectionCICIDS
A-R79.5
16
Multivariate Time Series Anomaly DetectionCICIDS
Precision0.3
16
Time-Series Anomaly DetectionCICIDS
AP (AUC-PR)0.003
16
Time Series Anomaly DetectionCICIDS
Affinity F178.7
16
Time Series Anomaly DetectionCICIDS
Affinity Precision66.7
16
Anomaly DetectionCICIDS
R-R0.986
16
Few-Shot Class Incremental LearningCICIDS 2017
PD43.96
16
Time Series Anomaly DetectionCICIDS
AUC-R82.76
13
Intrusion DetectionCICIDS 2017
Accuracy99.97
12
Adversarial DetectionCICIDS 2017
AUC-ROC99.8
12
Intrusion DetectionCICIDS18 (test)
Backward Transfer20.23
12
Intrusion DetectionCICIDS17 (test)
Backward Transfer7.84
12
Attack Detection RobustnessCICIDS 17
Attack F186.99
10
Network Traffic ClassificationCICIDS attack behavior shifts unseen domains 2017 (test)
Average Accuracy98.63
9
Network Security Threat DetectionCICIDS 2017
Precision0.9996
9
Intrusion DetectionCICIDS17 (clean)
Macro-F199.87
7
ClassificationCICIDS 2017 (stratified 5-fold cross-validation)
Accuracy93.88
6
Intrusion DetectionCICIDS 2017 (5-fold CV)
Macro-F174.81
6
Multi-class intrusion detectionCICIDS 2017 (test)
Accuracy99.6
6
Node-level anomaly detectionCICIDS 2017 (chronological)
ROC AUC0.9753
6
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