Intrusion Detection Model for Wireless Sensor Networks Based on FedAvg and XGBoost Algorithm
For the characteristics of channel instability in wireless sensor networks, this paper proposes an intrusion detection algorithm based on FedAvg (federated averaging) and XGBoost (extreme gradient boosting) wireless sensor networks using fog computing architecture. First, the network edge is extende...
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| Format: | Article |
| Language: | English |
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Wiley
2024-01-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | http://dx.doi.org/10.1155/2024/5536615 |
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| _version_ | 1832548315474952192 |
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| author | Hongjiao Wu |
| author_facet | Hongjiao Wu |
| author_sort | Hongjiao Wu |
| collection | DOAJ |
| description | For the characteristics of channel instability in wireless sensor networks, this paper proposes an intrusion detection algorithm based on FedAvg (federated averaging) and XGBoost (extreme gradient boosting) wireless sensor networks using fog computing architecture. First, the network edge is extended by introducing fog computing nodes to reduce the communication delay. It reduces the transmission bandwidth and privacy leakage risk while improving the accuracy of jointly learned global and local models. Then, the histogram-based approximation calculation method is improved to adapt to the unbalanced data characteristics of wireless sensor networks. Finally, by introducing TOP-K gradient selection, the number of model parameter uploads is minimized, and the efficiency of model parameter interaction is improved. The experimental results show that this algorithm has superior detection performance and low energy consumption. It is also compared with other algorithms to demonstrate the high detection rate and low computational complexity of this algorithm. |
| format | Article |
| id | doaj-art-23a98460af8e44059cbf5f45617dc412 |
| institution | Kabale University |
| issn | 1550-1477 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj-art-23a98460af8e44059cbf5f45617dc4122025-02-03T06:14:53ZengWileyInternational Journal of Distributed Sensor Networks1550-14772024-01-01202410.1155/2024/5536615Intrusion Detection Model for Wireless Sensor Networks Based on FedAvg and XGBoost AlgorithmHongjiao Wu0Henan Vocational College of TuinaFor the characteristics of channel instability in wireless sensor networks, this paper proposes an intrusion detection algorithm based on FedAvg (federated averaging) and XGBoost (extreme gradient boosting) wireless sensor networks using fog computing architecture. First, the network edge is extended by introducing fog computing nodes to reduce the communication delay. It reduces the transmission bandwidth and privacy leakage risk while improving the accuracy of jointly learned global and local models. Then, the histogram-based approximation calculation method is improved to adapt to the unbalanced data characteristics of wireless sensor networks. Finally, by introducing TOP-K gradient selection, the number of model parameter uploads is minimized, and the efficiency of model parameter interaction is improved. The experimental results show that this algorithm has superior detection performance and low energy consumption. It is also compared with other algorithms to demonstrate the high detection rate and low computational complexity of this algorithm.http://dx.doi.org/10.1155/2024/5536615 |
| spellingShingle | Hongjiao Wu Intrusion Detection Model for Wireless Sensor Networks Based on FedAvg and XGBoost Algorithm International Journal of Distributed Sensor Networks |
| title | Intrusion Detection Model for Wireless Sensor Networks Based on FedAvg and XGBoost Algorithm |
| title_full | Intrusion Detection Model for Wireless Sensor Networks Based on FedAvg and XGBoost Algorithm |
| title_fullStr | Intrusion Detection Model for Wireless Sensor Networks Based on FedAvg and XGBoost Algorithm |
| title_full_unstemmed | Intrusion Detection Model for Wireless Sensor Networks Based on FedAvg and XGBoost Algorithm |
| title_short | Intrusion Detection Model for Wireless Sensor Networks Based on FedAvg and XGBoost Algorithm |
| title_sort | intrusion detection model for wireless sensor networks based on fedavg and xgboost algorithm |
| url | http://dx.doi.org/10.1155/2024/5536615 |
| work_keys_str_mv | AT hongjiaowu intrusiondetectionmodelforwirelesssensornetworksbasedonfedavgandxgboostalgorithm |