Table 1 Accuracy comparison of existing IDS systems and Our Model (TP-IDS)
Sr. No. | IDS system | Accuracy (%) |
|---|---|---|
1. | IDS using SVM [7] | 93.85 |
2. | IDS using GRU-SVM [11] | 89.30 |
3. | IDS using LibSVM [13] | 98.64 |
4. | IDS using CAIDM [14] | 89.02 |
5. | IDS using PCA-FC-kNN [18] | 94.00 |
6. | IDS using BC-kNN [19] | 94.92 |
7. | IDS using WSN-kNN [20] | 89.90 |
8. | IDS using random forest [22] | 93.00 |
9. | IDS using decision tree [23] | 89.56 |
10. | IDS using naïve Bayes [24] | 95.00 |
11. | IDS using PCA and naïve Bayes [25] | 83.00 |
12. | IDS using MABC-PSO [27] | 98.67 |
13. | IDS using deep learning [30] (for known attacks only) | 99.77 |
14. | IDS using ANN [28] | 77.48 |
15. | IDS using ANN [29] (For known attacks only) | 99.25 |
16. | Our Model: TP-IDS | 99.93 |