Desensitization method of image data in the Internet of Vehicles based on instance segmentation

Shuang Li; Yue Zhou; Xin Zhang; Meng Zhang

doi:10.1117/12.2679260

8 May 2023 Desensitization method of image data in the Internet of Vehicles based on instance segmentation

Shuang Li, Yue Zhou, Xin Zhang, Meng Zhang

Proceedings Volume 12635, Second International Conference on Algorithms, Microchips, and Network Applications (AMNA 2023); 1263506 (2023) https://doi.org/10.1117/12.2679260
Event: International Conference on Algorithms, Microchips, and Network Applications 2023, 2023, Zhengzhou, China

Abstract

With the continuous development of intelligent connected vehicle industry, cameras and other vehicle-mounted devices are widely used, so the amount of data collection is increasing. There is a large amount of sensitive information hidden in the image data generated by connected vehicles. Once the data leakage event occurs, it may cause very serious consequences. In order to improve the security of connected vehicle data and reduce the threat of sensitive information leakage in image data, this paper provides a desensitization process of connected vehicle image data, and desensitizes sensitive information based on instance segmentation technology. In this paper, a real road image dataset is collected, and realizes desensitization of the modified dataset based on proposed framework.

Citation Download Citation

Shuang Li, Yue Zhou, Xin Zhang, and Meng Zhang "Desensitization method of image data in the Internet of Vehicles based on instance segmentation", Proc. SPIE 12635, Second International Conference on Algorithms, Microchips, and Network Applications (AMNA 2023), 1263506 (8 May 2023); https://doi.org/10.1117/12.2679260

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