A Random Binarization Scheme for Deep Face Feature Protection-Reference-Cited by-同舟云学术

A Random Binarization Scheme for Deep Face Feature Protection

Published:2020-10-15 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 4th International Conference on Computer Science and Application Engineering
language:
Short-container-title:

Author:

Xu Zhiqiang¹,Hao Dawei²,Wu Yi¹,Peng Jialiang³

Affiliation:

1. School of Data Science and Technology, Heilongjiang University, Harbin, China

2. Ordinance NCO academy, Army Engineering University of PLA, Wuhan, China

3. School of Data Science and Technology, Heilongjiang University, Harbin, China and Guangxi Key Laboratory of Cryptography and Information Security, Guilin, China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3424978.3425107

Reference17 articles.

1. Protection of Privacy in Biometric Data

2. A fuzzy commitment scheme

3. On application of bloom filters to iris biometrics

4. Face Template Protection Using Deep Convolutional Neural Network

5. Pavel Korshunov Sébastien Marcel (2018). DEEPFAKES: A New Threat to Face Recognition? Assessment and Detection[J]. Pavel Korshunov Sébastien Marcel (2018). DEEPFAKES: A New Threat to Face Recognition? Assessment and Detection[J].

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Biometric Cryptosystem with Deep Learning: A New Frontier in Security;2023 International Conference in Advances in Power, Signal, and Information Technology (APSIT);2023-06-09

2. Biometric Template Protection for Neural-Network-Based Face Recognition Systems: A Survey of Methods and Evaluation Techniques;IEEE Transactions on Information Forensics and Security;2023