Tao Zhang

Orcid: 0000-0002-3366-7640

Affiliations:
  • Beijing Jiaotong University, School of Cyberspace Science and Technology, Beijing, China
  • Beijing University of Posts and Telecommunications, State Key Laboratory of Networking and Switching Technology, Beijing, China (PhD 2023)


According to our database1, Tao Zhang authored at least 33 papers between 2018 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Bibliography

2025
An adaptive asynchronous federated learning framework for heterogeneous Internet of things.
Inf. Sci., 2025

2024
FedASA: A Personalized Federated Learning With Adaptive Model Aggregation for Heterogeneous Mobile Edge Computing.
IEEE Trans. Mob. Comput., December, 2024

Blockchain and Trusted Hardware-Enabled Data Scheduling for Edge Learning in Wireless IIoT.
IEEE Internet Things J., November, 2024

EPDB: An Efficient and Privacy-Preserving Electric Charging Scheme in Internet of Robotic Things.
IEEE Internet Things J., October, 2024

Securing Federated Diffusion Model With Dynamic Quantization for Generative AI Services in Multiple-Access Artificial Intelligence of Things.
IEEE Internet Things J., September, 2024

DecFFD: A Personalized Federated Learning Framework for Cross-Location Fault Diagnosis.
IEEE Trans. Ind. Informatics, May, 2024

Optimizing Resource Allocation for Multi-modal Semantic Communication in Mobile AIGC Networks: A Diffusion-based Game Approach.
CoRR, 2024

Hybrid-Generative Diffusion Models for Attack-Oriented Twin Migration in Vehicular Metaverses.
CoRR, 2024

Towards Secrecy Energy-Efficient RIS Aided UAV Network: A Lyapunov-Guided Reinforcement Learning Approach.
Proceedings of the IEEE Wireless Communications and Networking Conference, 2024

Energy Efficiency Maximization for Secure Live Video Streaming in UAV Wireless Networks.
Proceedings of the 99th IEEE Vehicular Technology Conference, 2024

A Dynamic Priority Packet Scheduling for UAV Assisted AoI-Aware Network: A Deep Reinforcement Learning Approach.
Proceedings of the 99th IEEE Vehicular Technology Conference, 2024

QoE Maximization for Video Streaming in Cache-Enable Satellite-UAV-Terrestrial Network.
Proceedings of the IEEE International Conference on Communications, 2024

Deep Reinforcement Learning-Based Moving Target Defense for Multicast in Software-Defined Satellite Networks.
Proceedings of the IEEE International Conference on Communications, 2024

On-demand Quantization for Green Federated Generative Diffusion in Mobile Edge Networks.
Proceedings of the IEEE International Conference on Communications, 2024

2023
When Moving Target Defense Meets Attack Prediction in Digital Twins: A Convolutional and Hierarchical Reinforcement Learning Approach.
IEEE J. Sel. Areas Commun., October, 2023

How to Mitigate DDoS Intelligently in SD-IoV: A Moving Target Defense Approach.
IEEE Trans. Ind. Informatics, 2023

How to Disturb Network Reconnaissance: A Moving Target Defense Approach Based on Deep Reinforcement Learning.
IEEE Trans. Inf. Forensics Secur., 2023

Towards Attack-Resistant Service Function Chain Migration: A Model-Based Adaptive Proximal Policy Optimization Approach.
IEEE Trans. Dependable Secur. Comput., 2023

Secure and Scalable Blockchain for IIoT with Dual Compression Scheme.
Proceedings of the 2023 IEEE International Conferences on Internet of Things (iThings) and IEEE Green Computing & Communications (GreenCom) and IEEE Cyber, 2023

An Overview of Enabling Artificial Intelligence in 3GPP 5G-Advanced Networks.
Proceedings of the 2023 IEEE International Conferences on Internet of Things (iThings) and IEEE Green Computing & Communications (GreenCom) and IEEE Cyber, 2023

Decentralized Reputation-based Leader Election for Privacy-preserving Federated Learning on Internet of Things.
Proceedings of the 2023 IEEE International Conferences on Internet of Things (iThings) and IEEE Green Computing & Communications (GreenCom) and IEEE Cyber, 2023

2022
Toward Attack-Resistant Route Mutation for VANETs: An Online and Adaptive Multiagent Reinforcement Learning Approach.
IEEE Trans. Intell. Transp. Syst., 2022

MARL-MOTAG: Multi-Agent Reinforcement Learning Based Moving Target Defense to thwart DDoS attacks.
Proceedings of the International Conference on Networking and Network Applications, 2022

CMT-MQ: Multi-QoS Aware Adaptive Concurrent Multipath Transfer With Reinforcement Learning.
Proceedings of the 2022 International Wireless Communications and Mobile Computing, 2022

Multi-Domain Multicast Routing Mutation Scheme for Resisting DDoS attacks.
Proceedings of the 2022 International Wireless Communications and Mobile Computing, 2022

2021
Context-Aware Adaptive Route Mutation Scheme: A Reinforcement Learning Approach.
IEEE Internet Things J., 2021

PPO-RM: Proximal Policy Optimization Based Route Mutation for Multimedia Services.
Proceedings of the 17th International Wireless Communications and Mobile Computing, 2021

2020
DQ-RM: Deep Reinforcement Learning-based Route Mutation Scheme for Multimedia Services.
Proceedings of the 16th International Wireless Communications and Mobile Computing Conference, 2020

2019
An Efficient and Agile Spatio-Temporal Route Mutation Moving Target Defense Mechanism.
Proceedings of the 2019 IEEE International Conference on Communications, 2019

A Reputation Management Scheme for Identifying Malicious Nodes in VANET.
Proceedings of the 20th IEEE International Conference on High Performance Switching and Routing, 2019

An Intelligent Route Mutation Mechanism against Mixed Attack Based on Security Awareness.
Proceedings of the 2019 IEEE Global Communications Conference, 2019

2018
Intelligent Routing Algorithm Based on Deep Belief Network for Multimedia Service in Knowledge Centric VANETs.
Proceedings of the International Conference on Networking and Network Applications, 2018

Event-based Diffusion Kalman Filter Strategy for Clock Synchronization in WSNs.
Proceedings of the International Conference on Networking and Network Applications, 2018


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