Controllable identity de-identification for face image

Bo Shen; Rui Zhang

doi:10.1117/12.2640874

2 December 2022 Controllable identity de-identification for face image

Bo Shen, Rui Zhang

Proceedings Volume 12288, International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2022); 1228817 (2022) https://doi.org/10.1117/12.2640874
Event: International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2022), 2022, Zhuhai, China

Abstract

Aiming at the problem that the face image recognition technology based on anonymization mechanism cannot provide quantifiable privacy guarantee and realize controllable privacy protection, a controllable face identity recognition method based on differential privacy mechanism and generative learning model was proposed. Based on the attentional mechanism and graph convolution network, this method designed a representation learning model to extract identity-related geometric and demographic information by exploring spatial and spatial semantic relationships between different facial regions. The differential privacy mechanism was used to protect the demographic attributes while preserving the geometric attributes of the face. Then generate adversarial network reconstruction image instead of original image release for computer vision analysis task. Experimental results show that the proposed method is superior to other models in terms of privacy and utility. It can effectively resist background knowledge attacks, reconstruction attacks, and combination attacks while realizing verifiable and controllable privacy protection of face identity and ensuring the optimal tradeoff between privacy and utility of published images.

Citation Download Citation

Bo Shen and Rui Zhang "Controllable identity de-identification for face image", Proc. SPIE 12288, International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2022), 1228817 (2 December 2022); https://doi.org/10.1117/12.2640874

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KEYWORDS

Facial recognition systems

Data modeling

Image quality

Image processing

Visualization

Convolution

Evolutionary algorithms

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