Privacy protection method for ADS-B air traffic control data based on convolutional neural network and symmetric encryption

Compared to existing methods, our approach achieves shorter encryption times while maintaining robust privacy protection. Future work could explore integrating advanced encryption technologies with state-of-the-art deep learning algorithms to further enhance the security of privacy protection in ADS-B systems.

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Publication Details

Journal
Frontiers in Big Data
Published
2025-12-18
DOI
https://doi.org/10.3389/fdata.2025.1683027
Primary Topic
Air Traffic Management and Optimization
Type
article
Field-Weighted Citation Impact
0.00
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article

Privacy protection method for ADS-B air traffic control data based on convolutional neural network and symmetric encryption

Ruchun Jia, Jing Lou, Mingqian Wang, Changsheng Ma
Frontiers in Big Data
Air Traffic Management and Optimization
article

Privacy protection method for ADS-B air traffic control data based on convolutional neural network and symmetric encryption

Ruchun Jia, Jing Lou, Mingqian Wang, Changsheng Ma
article en

Abstract

Compared to existing methods, our approach achieves shorter encryption times while maintaining robust privacy protection. Future work could explore integrating advanced encryption technologies with state-of-the-art deep learning algorithms to further enhance the security of privacy protection in ADS-B systems.

Frontiers in Big DataVol. 8
Sichuan University (CN), Changzhou Institute of Mechatronic Technology (CN)
Openalex Percentile: Top 48%
Air Traffic Management and Optimization
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