共 50 条
[41]
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
[44]
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
[45]
Federated Learning Framework Based on Distributed Storage and Diffusion Model for Intrusion Detection on IoT Networks
[J].
IEEE ACCESS,
2025, 13
:79571-79595
[48]
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
[49]
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
[50]
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,