Research on Intelligent Network Security Event Detection and Emergency Disposal Technology
31 mars 2025
À propos de cet article
Publié en ligne: 31 mars 2025
Reçu: 11 nov. 2024
Accepté: 14 févr. 2025
DOI: https://doi.org/10.2478/amns-2025-0819
Mots clés
© 2025 Wang Xiaoxia, published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.
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Identification of different types of attacks in different models
| Attack type | Model | Precision | accuracy | Recall | F1 score |
|---|---|---|---|---|---|
| CNN-LSTM_HMNID | 0.95 | 0.96 | 0.94 | 0.945 | |
| DDoS attack | SVM | 0.90 | 0.92 | 0.88 | 0.89 |
| Random Forest | 0.92 | 0.93 | 0.90 | 0.91 | |
| CNN-LSTM_HMNID | 0.93 | 0.95 | 0.96 | 0.945 | |
| Port scanning | SVM | 0.88 | 0.90 | 0.92 | 0.90 |
| Random Forest | 0.90 | 0.92 | 0.91 | 0.905 | |
| CNN-LSTM_HMNID | 0.91 | 0.93 | 0.92 | 0.915 | |
| phishing | SVM | 0.85 | 0.87 | 0.86 | 0.855 |
| Random Forest | 0.87 | 0.89 | 0.88 | 0.875 |
Accuracy and false alarm rate of model recognition
| data set | Network traffic type | Recognition accuracy (%) | False alarm rate (%) |
|---|---|---|---|
| Normal flow | 98.5 | 1.5 | |
| Data set 1 | Abnormal traffic (DDoS attack) | 96.2 | 3.8 |
| Abnormal traffic (port scanning) | 97.8 | 2.2 | |
| Normal flow | 97.7 | 2.3 | |
| Data set 2 | Abnormal traffic (phishing) | 95.5 | 4.5 |
| Abnormal traffic (malware download) | 98.2 | 1.8 | |
| Comprehensive data set | All traffic types | 97.3 | 2.7 |
Performance evaluation index
| Performance index | Normal flow | Abnormal flow |
|---|---|---|
| Precision | 0.97 | 0.95 |
| Recall | 0.98 | 0.96 |
| F1 Score | 0.975 | 0.955 |