Article | Classification Technique | Results | |||||||||||
Accuracy | TT (sec) | prediction | TP | TN | FP | FN | Error rate | Precision | Recall | DR | FAR | ||
3: Detecting anomaly based network intrusion using feature extraction and classification techniques | Decision Tree | 95.09% | 1.032 | 0.003 | 4649 | 2702 | 279 | 100 | 4.9 | 94.34% | 97.34% | . | , |
MLP | 92.46% | 20.59 | 0.004 | 4729 |
| 2419 | 562 | 29 | 7.54 | 89.38 | 99.56% |
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KNN | 92.78% | 82.956 | 13.24 | 4726 | 2446 | 535 | 23 | 7.22 | 89.83% | 99.52% |
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Linear SVM | 92.59% | 78.343 | 2.11 | 4723 | 2434 | 547 | 26 | 7.41 | 89.62% | 99.45% |
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Passive aggressive | 90.34 | 0.275 | 0.001 | 4701 | 2282 | 699 | 48 | 9.66 | 89.62% | 99.45% |
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RBF SVM | 91.67% | 99.47 | 2.547 | 4726 | 2960 | 621 | 23 | 8.33 | 89.39% | 99.52% |
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Random Forest | 93.62% | 1.189 | 0.027 | 4677 | 2560 | 621 | 23 | 6.38 | 91.74% | 98.48% |
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AdaBoost | 93.52% | 29.556 | 0.225 | 4676 | 2553 | 428 | 73 | 6.48 | 91.61% | 98.46% |
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Gausian NB | 94.35% | 244 | 0.006 | 4642 | 2651 | 330 | 107 | 5.65 | 93.36% | 97.75% | - | - | |
MultionmINB | 91.71% | 0.429 | 0.001 | 4732 | 2357 | 624 | 17 | 8.29 | 88.35% | 99.64% | - | - | |
Adratic Discriminat Ana | 93.23% | 1.305 | 0.0019 | 4677 | 2530 | 451 | 72 | 6.77 | 91.20% | 84.87% | - | - |