IoT Attack Detection on IoTGeM Cross-Dataset (test) benchmark leaderboard · SOTA2 Research

IoT Attack Detection on IoTGeM Cross-Dataset (test)

100F1 ScoreDT

Evaluation Results

Method	Links
DT2023.10		100
RF2023.10		100
XGB2023.10		100
RF2023.10		100
XGB2023.10		100
LR2023.10		99.8
NB2023.10		99.8
KNN2023.10		99.7
LR2023.10		99.7
MLP2023.10		99.7
MLP2023.10		99.5
KNN2023.10		99.3
RF2023.10		98.9
XGB2023.10		98.9
LR2023.10		98.6
RF2023.10		98.5
LR2023.10		98.1
NB2023.10		97.1
XGB2023.10		94.5
NB2023.10		94.1
DT2023.10		93
DT2023.10		91.2
XGB2023.10		91.2
DT2023.10		89.6
DT2023.10		88.9
RF2023.10		86.2
NB2023.10		83.3
MLP2023.10		81.2
XGB2023.10		81.1
DT2023.10		79.5
MLP2023.10		78.1
KNN2023.10		75.6
NB2023.10		73.8
NB2023.10		72.6
LR2023.10		69.1
RF2023.10		68.4
LR2023.10		63.9
RF2023.10		61.8
SVM2023.10		58.7
LR2023.10		56.7
SVM2023.10		55.6
XGB2023.10		55.1
DT2023.10		54.2
KNN2023.10		52
SVM2023.10		49.5
MLP2023.10		48.6
SVM2023.10		46.1
KNN2023.10		45.7
DT2023.10		45.4
NB2023.10		45.3
LR2023.10		40.2
MLP2023.10		38.8
RF2023.10		37.7
MLP2023.10		37.3
DT2023.10		35.9
NB2023.10		35.6
KNN2023.10		35.5
DT2023.10		35.1
XGB2023.10		34.9
RF2023.10		34.5
KNN2023.10		34.1
MLP2023.10		33.3
SVM2023.10		33.3
SVM2023.10		33.3
SVM2023.10		33.3
SVM2023.10		33.3
MLP2023.10		33.3
SVM2023.10		33.3
MLP2023.10		33.2
NB2023.10		32.9
RF2023.10		31.7
SVM2023.10		31.3
XGB2023.10		31.3
LR2023.10		31
KNN2023.10		29.8
KNN2023.10		21.8
LR2023.10		21.8
XGB2023.10		21.8
KNN2023.10		21.2
NB2023.10		21.2