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With the increasing importance of satellite communications in B5G/6G networks, satellite network security has become a critical issue. In this paper, distinct from existing literature that primarily focuses on Distributed Denial of Service (DDoS) attack detection schemes for the uplink between ground nodes and satellite nodes, we propose a detection method specifically targeting low-rate DDoS attacks between satellite nodes in multilayer satellite networks. By combining the AlexNet convolutional neural network and the Random Forest (RF) model to construct an ensemble of small models, the proposed method effectively identifies and classifies low-rate DDoS attack traffic originating from satellite nodes. To adapt to the special characteristics of satellite networks, we designed tunnels based on the Delay-Tolerant Networking (DTN) architecture to enable the conversion between the IP stack and the Bundle Protocol (BP) stack. Experimental results demonstrate that the proposed method outperforms existing models regarding precision and F1 score for attack detection. It provides effective security protection for key nodes of multilayer satellite networks and has good potential for practical application.

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A DDoS Attack Detection Method Based on an Ensemble of Small Models for Multi-layer Satellite Networks

  • 会议论文

  • 发表日期：

    2026年

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  • Xiaojing Fan,
  • Wangjian Zhou,
  • Huachun Zhou

摘要

With the increasing importance of satellite communications in B5G/6G networks, satellite network security has become a critical issue. In this paper, distinct from existing literature that primarily focuses on Distributed Denial of Service (DDoS) attack detection schemes for the uplink between ground nodes and satellite nodes, we propose a detection method specifically targeting low-rate DDoS attacks between satellite nodes in multilayer satellite networks. By combining the AlexNet convolutional neural network and the Random Forest (RF) model to construct an ensemble of small models, the proposed method effectively identifies and classifies low-rate DDoS attack traffic originating from satellite nodes. To adapt to the special characteristics of satellite networks, we designed tunnels based on the Delay-Tolerant Networking (DTN) architecture to enable the conversion between the IP stack and the Bundle Protocol (BP) stack. Experimental results demonstrate that the proposed method outperforms existing models regarding precision and F1 score for attack detection. It provides effective security protection for key nodes of multilayer satellite networks and has good potential for practical application.