A Learning-based Honeypot Game for Collaborative Defense in UAV Networks-Reference-Cited by-同舟云学术

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A Learning-based Honeypot Game for Collaborative Defense in UAV Networks

Published:2022-12-04 Issue: Volume: Page:
ISSN:
Container-title:GLOBECOM 2022 - 2022 IEEE Global Communications Conference
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Author:

Wang Yuntao¹,Su Zhou¹,Benslimane Abderrahim²,Xu Qichao³,Dai Minghui⁴,Li Ruidong⁵

Affiliation:

1. Xi'an Jiaotong University,School of Cyber Science and Engineering,China

2. Avignon University,Laboratory of Computer Sciences,France

3. Shanghai University,School of Mechatronic Engineering and Automation,China

4. University of Macau,State Key Laboratory of Internet of Things for Smart City,Macau,China

5. Kanazawa University,Department of Electrical and Computer Engineering,Japan

Funder

NSFC

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10000063/10000593/10000872.pdf?arnumber=10000872

Reference13 articles.

1. Spectrum Trading in Cognitive Radio Networks: A Contract-Theoretic Modeling Approach

2. Energy Minimization for Wireless Communication With Rotary-Wing UAV

3. Contract-Based Incentive Mechanisms for Honeypot Defense in Advanced Metering Infrastructure

4. Drones in Distress: A Game-Theoretic Countermeasure for Protecting UAVs Against GPS Spoofing

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Federated Learning based Vehicular Threat Sharing: A Multi-Dimensional Contract Incentive Approach;2023 IEEE 98th Vehicular Technology Conference (VTC2023-Fall);2023-10-10

2. Towards an Adversarial Machine Learning Framework in Cyber-Physical Systems;2023 IEEE/ACIS 21st International Conference on Software Engineering Research, Management and Applications (SERA);2023-05-23

3. Collaborative Honeypot Defense in UAV Networks: A Learning-Based Game Approach;IEEE Transactions on Information Forensics and Security;2023

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