Lightweight Intrusion Detection in IoT via SHAP-Guided Feature Pruning and Knowledge-Distilled Kronecker Networks

Ähnliche Einträge

• Efficient Intrusion Detection: Combining $χ^2$ Feature Selection with CNN-BiLSTM on the UNSW-NB15 Dataset
  von: Jouhari, Mohammed, et al.
  Veröffentlicht: (2024)
• Lightweight CNN-BiLSTM based Intrusion Detection Systems for Resource-Constrained IoT Devices
  von: Jouhari, Mohammed, et al.
  Veröffentlicht: (2024)
• OptiFLIDS: Optimized Federated Learning for Energy-Efficient Intrusion Detection in IoT
  von: Elouardi, Saida, et al.
  Veröffentlicht: (2025)
• Lightweight Cluster-Based Federated Learning for Intrusion Detection in Heterogeneous IoT Networks
  von: Izadi, Saadat, et al.
  Veröffentlicht: (2026)
• Efficient Network Traffic Feature Sets for IoT Intrusion Detection
  von: Silva, Miguel, et al.
  Veröffentlicht: (2024)