Deep Reinforcement Learning-Based Moving Target Defense for Multicast in Software-Defined Satellite Networks-Reference-Cited by-同舟云学术

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Deep Reinforcement Learning-Based Moving Target Defense for Multicast in Software-Defined Satellite Networks

Published:2024-06-09 Issue: Volume: Page:4786-4791
ISSN:
Container-title:ICC 2024 - IEEE International Conference on Communications
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Author:

Lian Yibo¹,Zhang Tao²,Xu Changqiao¹,Dong Wei¹,Xu Minrui³,Xiahou Zhenyu⁴,Kang Jiawen⁵,Liu Jiqiang²,Niyato Dusit³

Affiliation:

1. School of Computer Science, Beijing University of Posts and Telecommunications

2. School of Software Engineering, Beijing Jiaotong University

3. School of Computer Science and Engineering, Nanyang Technological University

4. Jiangxi Academy of Cyber Security

5. School of Automation, Guangdong University of Technology

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10622104/10622158/10622302.pdf?arnumber=10622302

Reference23 articles.

1. Security and Privacy on 6G Network Edge: A Survey

2. Marine IoT Systems With Space–Air–Sea Integrated Networks: Hybrid LEO and UAV Edge Computing

3. A Survey on Technologies, Standards and Open Challenges in Satellite IoT

4. On a Novel High Accuracy Positioning With Intelligent Reflecting Surface and Unscented Kalman Filter for Intelligent Transportation Systems in B5G

5. Software defined satellite networks: A survey

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