Research Article
Balancing Data Privacy and 5G VNFs Security Monitoring: Federated Learning with CNN + BiLSTM + LSTM Model
Table 11
Proposed model compared with previous works (traditional learning).
| Reference | Year | Technique used | Dataset utilized | Accuracy (%) | FPR (%) |
| Proposed model | 2023 | CNN-BiLSTM-LSTM | InSDN CICIDS2017 | 99.99 99.68 | 0.0089 0.39 | [31] | 2022 | CNN | CICIDS2017 | 99.0 | 0.67 | [26] | 2020 | DBN | CICIDS2017 | 97.73 | — | [24] | 2021 | Hybrid CNN | InSDN | 99.28 | — | [51] | 2021 | DFFNN | NSL-KDD UNSW-NB15 | 99.0 98.9 | 1.0 1.1 | [52] | 2022 | LSTM-BiLSTM-GRU-BiGRU | NSL-KDD UNSW-NB15 | 87.44 82.46 | 20.47 37.61 | [53] | 2022 | MLP | UNSW-NB15 | 96.7 | — |
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