Table 15 List of studies using ANNs approaches, dataset and performance metric for IoT DoS/DDoS detection
Ref. | Dataset | Performance evaluation parameters |
|---|---|---|
[117] | NSL-KDD | Accuracy, Recall, No of features |
[118] | KDD CUP 1999 | Precision, Accuracy, Recall and F1-score |
[17] | DS2OS traffic traces | Accuracy, Precision, Recall and F1-score |
[18] | CICIDS2017 | Precision, Accuracy and Recall |
[19] | Data collected from local network | Accuracy, Specificity, Sensitivity/Recall and Precision |
[20] | Bot-IoT | TPR (True Positive Rate), FPR (False positive Rate), Precision, Recall, Accuracy, F1-score |
[21] | IoT network-traffic | Precision, Recall, Accuracy, F1-score |
[168] | Own | Sensitivity/Recall, Specificity, FPR, FNR, Precision |
[111] | Network traffic file | Accuracy, Precision, Sensitivity |
[169] | CIDDS-001 | Accuracy, Precision, Recall, FPR |
[120] | DS2OS traffic traces | Accuracy, Precision, Recall F1-score |
[116] | UNSW-NB15 dataset | Accuracy, Precision, Recall, F1-score, Miscalculation rate |
[157] | Consumer IoT DoS attack traffic | Accuracy, Precision, Recall, F1-score |
[108] | UNSW-15 dataset | Accuracy, Precision, Detection rate, Dataset size, No of attacks |
[123] | UCLA Dataset | Accuracy, Detection rate, FPR,FNR, TNR, TPR |
[114] | Aegean Wi-Fi Intrusion dataset | Accuracy, Precision, Recall, F-measure |
[163] | Own dataset | Accuracy, Precision, Recall, F-measure |
[106] | IoT generated dataset | Accuracy, Precision, Recall, F-measure |
[170] | Own dataset | Accuracy, Precision, Recall, F-measure |
[139] | CICIDS dataset | Accuracy, Precision, Recall, F-measure |
[141] | NSL-KDD dataset | Accuracy, Precision, Recall, F-measure, False alarm |
[129] | KDD Cup 1999 | Accuracy, Detection rate, False alarm rate |
[158] | NSL-KDD dataset | Accuracy, Precision, Detection rate, True positive rate, True negative rate, False positive rate, False negative rate |
[159] | KDDCUP99 dataset | Precision, Recall, Accuracy, Detection rate, FAR (False alarm rate) |
[160] | CICDDoS2019 | Accuracy, FAR, Detection rate, Precision |
[45] | KDDCUP99 dataset and custom dataset | Accuracy |
[161] | VeReMi Extension dataset | Precision, Accuracy, Recall, F1-score |
[162] | IoT-Botnet 2020 | Precision, Recall, Accuracy, F1-score, True-negative rate (TNR), False alarm rate (FAR), False-negative rate (FNR) |