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Secure Data Transmission Based on Reinforcement Learning and Position Confusion for Internet of UAVs

文献类型： 外文期刊

作者： Zhu, Xiuzhen 1 ; Lin, Limei 1 ; Huang, Yanze 2 ; Wang, Xiaoding 1 ; Que, Youxiong 3 ; Jedari, Behrouz 5 ; Piran, Md. Jalil 6 ;

作者机构： 1.Fujian Normal Univ, Fujian Prov Key Lab Network Secur & Cryptol, Coll Comp & Cyber Secur, Fuzhou 350117, Fujian, Peoples R China

2.Fujian Univ Technol, Sch Comp Sci & Math, Fujian Prov Key Lab Big Data Min & Applicat, Fuzhou 350118, Peoples R China

3.Chinese Acad Trop Agr Sci, Inst Trop Biosci & Biotechnol, Natl Key Lab Trop Crop Breeding, Sanya 572024, Peoples R China

4.Fujian Agr & Forestry Univ, Minist Agr & Rural Affairs, Key Lab Sugarcane Biol & Genet Breeding, Fuzhou 350002, Fujian, Peoples R China

5.Nokia Electr Ltd, RAN L1, Espoo 02610, Finland

6.Sejong Univ, Dept Comp Sci & Engn, Seoul 05006, South Korea

关键词： Autonomous aerial vehicles; Security; Task analysis; Routing; Network topology; Electronic mail; Reinforcement learning; Message authentication; position confusion; reinforcement learning; unmanned aerial vehicles (UAVs)

期刊名称：IEEE INTERNET OF THINGS JOURNAL （ 影响因子：8.2； 五年影响因子：9.0 ）

ISSN： 2327-4662

年卷期： 2024 年 11 卷 12 期

页码：

收录情况： SCI

摘要： Ensuring the stability and security of unmanned aerial vehicle (UAV) communication, especially during long-distance missions, is essential for safeguarding against potential attacks. Large-scale UAV communication faces challenges, including eavesdropping threat, data tampering, replay threat, and man-in-the-middle threat. We propose a security information transmission solution based on reinforcement learning and location confusion algorithm (RLPC-SIT) to achieve a secure data transmission between UAVs. First, we leverage the principles of reinforcement learning to identify the most stable transmission routes. Second, we employ location confusion techniques to blur each location of the transmitting UAV with respect to other UAVs. Furthermore, we utilize the concept of message authentication to encrypt the transmitted data, thus making it inaccessible to malicious nodes and preventing forgery. The results of our theoretical analysis and simulation-based experiments indicate that our approach outperforms other security schemes.

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