Vulnerability of State-of-the-Art Face Recognition Models to Template Inversion Attack-Reference-Cited by-同舟云学术

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Vulnerability of State-of-the-Art Face Recognition Models to Template Inversion Attack

Published:2024 Issue: Volume:19 Page:4585-4600
ISSN:1556-6013
Container-title:IEEE Transactions on Information Forensics and Security
language:
Short-container-title:IEEE Trans.Inform.Forensic Secur.

Author:

Otroshi Shahreza Hatef¹^ORCID,Hahn Vedrana Krivokuća¹^ORCID,Marcel Sébastien¹^ORCID

Affiliation:

1. Biometrics Security and Privacy Group, Idiap Research Institute, Martigny, Switzerland

Funder

Horizon 2020 Marie Skłodowska-Curie TRaining in Secure and PrivAcy-preserving biometricS Early Training Networks

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/10206/10319981/10478940.pdf?arnumber=10478940

Reference70 articles.

1. On the vulnerability of face verification systems to hill-climbing attacks

2. Adversarial Biometric Recognition : A review on biometric system security from the adversarial machine-learning perspective

3. Handbook of Biometric Anti-Spoofing

4. Face Reconstruction from Deep Facial Embeddings using a Convolutional Neural Network

5. Enhancing security and privacy in biometrics-based authentication systems

Cited by 1 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. Facial Emotion Recognition for Virtual Customer Service Agents;2024 International Conference on Communication, Computer Sciences and Engineering (IC3SE);2024-05-09

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