共 50 条
- [32] Computationally Efficient Deep Federated Learning with Optimized Feature Selection for IoT Botnet Attack Detection [J]. INTELLIGENT SYSTEMS WITH APPLICATIONS, 2025, 25
- [34] Design a Robust DDoS Attack Detection and Mitigation Scheme in SDN-Edge-IoT by Leveraging Machine Learning [J]. IEEE ACCESS, 2025, 13 : 10194 - 10214
- [35] Collaborative Federated Learning for 6G With a Deep Reinforcement Learning-Based Controlling Mechanism: A DDoS Attack Detection Scenario [J]. IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT, 2024, 21 (04): : 4731 - 4749
- [36] DDoS Attack Detection via Privacy-aware Federated Learning and Collaborative Mitigation in Multi-domain Cyber Infrastructures [J]. PROCEEDINGS OF THE 2022 IEEE 11TH INTERNATIONAL CONFERENCE ON CLOUD NETWORKING (IEEE CLOUDNET 2022), 2022, : 118 - 125
- [38] FedMADE: Robust Federated Learning for Intrusion Detection in IoT Networks Using a Dynamic Aggregation Method [J]. INFORMATION SECURITY, PT II, ISC 2024, 2025, 15258 : 286 - 306
- [39] Federated Learning-Based Intrusion Detection in the Context of IIoT Networks: Poisoning Attack and Defense [J]. NETWORK AND SYSTEM SECURITY, NSS 2021, 2021, 13041 : 131 - 147
- [40] An Abnormal Traffic Detection Method for IoT Devices Based on Federated Learning and Depthwise Separable Convolutional Neural Networks [J]. 2022 IEEE INTERNATIONAL PERFORMANCE, COMPUTING, AND COMMUNICATIONS CONFERENCE, IPCCC, 2022,