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Differential Privacy Data Protection for Internet of Vehicle by Combining Federated Learning and Reinforced Learning
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Zhongping Wu1, Zongbo Hao2, Wenjing Wang3, Dong Liu4
Automobile Technology | 2023, (11) : 56 - 62
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Automobile Technology | 2023, (11): 56-62
Differential Privacy Data Protection for Internet of Vehicle by Combining Federated Learning and Reinforced Learning
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Zhongping Wu1, Zongbo Hao2, Wenjing Wang3, Dong Liu4
Affiliations
  • 1 Chengdu Institute of Technology, Chengdu 611730
  • 2 University of Electronic Science and Technology of China, Chengdu 610054
  • 3 Taiyuan Normal University, Jinzhong 030619
  • 4 Chengdu Desca Technology Co., Ltd., Chengdu 610097
Published: 2023-11-24 doi: 10.19620/j.cnki.1000-3703.20230294
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To ensure the security and privacy of sensitive data in Internet of Vehicle (IoV) environments, this paper proposed a distributed differential privacy data protection scheme combining federated learning and reinforced learning mechanisms. In this scheme, a federated learning architecture was applied to keep data on vehicle nodes or edge devices for learning, enabling data privacy protection, reducing data transmission costs through distributed storage. The Laplace mechanism was employed to achieve differential privacy, the Layer-wise Relevance Propagation (LRP) was used to manage data perturbation, ensuring the privacy and efficiency of model parameter transmissions. Experimental results show that the proposed scheme can achieve approximately 80% global accuracy within 10 rounds of communication, with a maximum of 98%, can complete model aggregation within less communication rounds, achieving a good balance between privacy protection and global data accuracy, and accurately detecting the injection of false noise through the reinforced learning strategy, promoting the intelligence and security levels of IoV.

Internet of vehicle  /  Federated learning  /  Reinforced learning  /  Differential privacy  /  Laplace mechanism  /  Layer-wise relevance propagation
Zhongping Wu, Zongbo Hao, Wenjing Wang, Dong Liu. Differential Privacy Data Protection for Internet of Vehicle by Combining Federated Learning and Reinforced Learning[J]. Automobile Technology, 2023 , (11) : 56 -62 . DOI: 10.19620/j.cnki.1000-3703.20230294
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doi: 10.19620/j.cnki.1000-3703.20230294
  • Online Date：2025-12-07
  • Published：2023-11-24
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  • Revised：2023-06-09
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Affiliations
    1 Chengdu Institute of Technology, Chengdu 611730
    2 University of Electronic Science and Technology of China, Chengdu 610054
    3 Taiyuan Normal University, Jinzhong 030619
    4 Chengdu Desca Technology Co., Ltd., Chengdu 610097
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https://castjournals.cast.org.cn/joweb/qcjs/EN/10.19620/j.cnki.1000-3703.20230294
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