HFDRL: An Intelligent Dynamic Cooperate Cashing Method Based on Hierarchical Federated Deep Reinforcement Learning in Edge-Enabled IoT
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Internet of Things Journal"
DOI: 10.1109/jiot.2021.3086623
Abstract: The Internet of Things (IoT) has significantly increased the number of terminals and network traffic. It is necessary to exploit the full capacity of the network and optimize content transfer. Despite the powerful processing and… read more here.
Keywords: federated deep; reinforcement learning; deep reinforcement; hierarchical federated ... See more keywords
Privacy-Preserving Federated Deep Learning With Irregular Users
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Dependable and Secure Computing"
DOI: 10.1109/tdsc.2020.3005909
Abstract: Federated deep learning has been widely used in various fields. To protect data privacy, many privacy-preservingapproaches have been designed and implemented in various scenarios. However, existing works rarely consider a fundamental issue that the data… read more here.
Keywords: federated deep; preserving federated; irregular users; privacy preserving ... See more keywords
MI-VFDNN: An Efficient Vertical Federated Deep Neural Network With Multi-Layer Interaction
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Transactions on Information Forensics and Security"
DOI: 10.1109/tifs.2024.3435557
Abstract: Federated Learning (FL) is proposed to address the challenge of data isolation, with federated machine learning algorithms continuously evolving. Vertical Federated Learning (VFL) is a specific FL setting where parties possessing different features but the… read more here.
Keywords: federated deep; vfdnn efficient; efficient vertical; vertical federated ... See more keywords
Federated Deep Reinforcement Learning for RIS-Assisted Indoor Multi-Robot Communication Systems
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Vehicular Technology"
DOI: 10.1109/tvt.2022.3190557
Abstract: Indoor multi-robot communications face two key challenges: one is the severe signal strength degradation caused by blockages (e.g., walls) and the other is the dynamic environment caused by robot mobility. To address these issues, we… read more here.
Keywords: federated deep; reinforcement learning; deep reinforcement; indoor multi ... See more keywords
Mitigating Jamming Attack in 5G Heterogeneous Networks: A Federated Deep Reinforcement Learning Approach
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Vehicular Technology"
DOI: 10.1109/tvt.2022.3212966
Abstract: Jamming attack is one of the serious security breaches in the upcoming fifth-generation heterogeneous networks (5G HetNets). Most of the existing anti-jamming techniques, such as frequency hopping (FH) and direct sequence spread spectrum (DSSS) lack… read more here.
Keywords: federated deep; reinforcement learning; reinforcement; deep reinforcement ... See more keywords