Privacy protection based on mask template
Hao Wang (1), Yu Bai (2), Guangmin Sun (1), Jie Liu (1) ((1) Beijing, University of Technology,(2) Beijing Friendship Hospital)

TL;DR
This paper proposes a privacy protection method using mask templates to prevent unauthorized recognition algorithms from extracting personal biometric features from images, addressing privacy concerns in digital recognition systems.
Contribution
It introduces a novel mask template approach to obscure biometric data in images, enhancing privacy protection against unauthorized recognition.
Findings
Effective in concealing biometric features
Compatible with existing recognition algorithms
Enhances privacy without compromising image usability
Abstract
Powerful recognition algorithms are widely used in the Internet or important medical systems, which poses a serious threat to personal privacy. Although the law provides for diversity protection, e.g. The General Data Protection Regulation (GDPR) in Europe and Articles 1032 to 1039 of the civil code in China. However, as an important privacy disclosure event, biometric data is often hidden, which is difficult for the owner to detect and trace to the source. Human biometrics generally exist in images. In order to avoid the disclosure of personal privacy, we should prevent unauthorized recognition algorithms from acquiring the real features of the original image.
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Taxonomy
TopicsDigital Media and Visual Art
