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Similarly, when recovering the service feature, we get an accuracy greater than 0.89 for the 10 most frequent values of this feature and a noisy F1 score with a higher value of 0.96. In Table 3, we present the confusion matrix for the recovery of the three values of the feature: ‘protocol’. This is information similar to that given for the classification case (Section 4.1). Table 4 also shows detailed performance metrics such as those provided for the classification case. We only present detailed data (as in Tables 3-4) for the case of recovery of the feature: ‘protocol’. Similar data could be presented for the other two discrete features, but their large number of values would provide too much information to be useful for analysis. The description of the data presented in Tables 3-4 is similar to the data presented in Table 1 and Figure 6. Table 3. Confusion matrix for reconstruction of all features values when feature: ‘protocol’ is missing. Prediction icmp tcp udp Total Percentage (%) 1022 13 7 1042 4.62% 19 2 18791 76 79 2535 18889 2613 83.79% 11.59% 1043 18880 2621 22544 100.00% 4.63% 83.75% 11.63% 100.00% Ground Truth tcp udp Total Percentage (%) Table 4. Detailed performance metrics for reconstruction of all features values when feature: ‘protocol’ is missing. Label value Frequency Accuracy 83.75% 0.9917 0.9950 11.63% 0.9927 0.9687 4.63% 0.9982 0.9803 0.9948 0.9953 0.0267 0.9701 0.9672 0.0039 0.9808 0.9799 0.0009 0.9757 0.9957 0.9990 F1 Precision Recall FPR NPV tcp udp icmp icmp So far, we have only covered the reconstruction of discrete features. However, we have also done the experiment to recover all continuous features using only the three discrete features to perform the recovery. We obtained a Root Mean Square Error (RMSE) of 0.1770 when retrieving the 32 continuous features from the discrete features. All performance metrics are calculated using the full NSL-KDD test dataset. 4.3. Model Training These are lessons learned about training the models: The inclusion of drop-out as regularization gives worse results. Having more than two or three layers for the encoder or Doctoral Thesis: Novel applications of Machine Learning to NTAP - 143PDF Image | Novel applications of Machine Learning to Network Traffic Analysis
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