Advances, Systems and Applications
Table 5 the binary classification results of EHIDS, CF-OSELM-PRFF, ABA-IDS, and ICNN-FCID.
From: Enhancement of an IoT hybrid intrusion detection system based on fog-to-cloud computing
Data set | Comparison criteria | EHIDS | CF-OSELM-PRFF | ABA-IDS | ICNN-FCID |
|---|---|---|---|---|---|
UNSW-NB15 Data Set | Accuracy | 96.47% | 94.70% | 90.88% | 92.38% |
Precision score | 96.53% | 94.94% | 82.50% | 94.44% | |
Recall score | 96.47% | 93.12% | 91.37% | 88.41% | |
F-score | 96.47% | 93.54% | 86.83% | 90.66% | |
ToN_IoT Data Set | Accuracy | 95.36% | 91.31% | 90.03% | 92.26% |
Precision score | 99.02% | 95.27% | 94.05% | 95.51% | |
Recall score | 99.04% | 93.12% | 94.05% | 94.43% | |
F-score | 99.02% | 93.54% | 94.05% | 91.66% |