Transformer Based Defense GAN Against Palm-Vein Adversarial Attacks

Author:

Li Yantao1ORCID,Ruan Song1ORCID,Qin Huafeng2ORCID,Deng Shaojiang1ORCID,El-Yacoubi Mounim A.3ORCID

Affiliation:

1. College of Computer Science, Chongqing University, Chongqing, China

2. School of Computer Science and Information Engineering, Chongqing Technology and Business University, Chongqing, China

3. SAMOVAR, Telecom SudParis, CNRS, Institut Polytechnique de Paris, Palaiseau, France

Funder

Scientific Innovation 2030 Major Project for New Generation of Artificial Intelligence

National Natural Science Foundation of China

Fellowship of China Post-Doctoral Science Foundation

Science Fund for Creative Research Groups of Chongqing Universities

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Networks and Communications,Safety, Risk, Reliability and Quality

Cited by 6 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. Tracing footprints of anti-forensics and assuring secured data transmission in the cloud using an effective ECCDH and Kalman Filter;Journal of Network and Computer Applications;2024-01

2. AG-NAS: An Attention GRU-Based Neural Architecture Search for Finger-Vein Recognition;IEEE Transactions on Information Forensics and Security;2024

3. Lightweight CNN and Image Enhancement Using in Palm Vein Recognition;2023 Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC);2023-10-31

4. Adversarial Contrastive Learning Based on Image Generation for Palm Vein Recognition;2023 2nd International Conference on Artificial Intelligence and Intelligent Information Processing (AIIIP);2023-10-27

5. Towards Inference of Original Graph Data Information from Graph Embeddings;2023 International Joint Conference on Neural Networks (IJCNN);2023-06-18

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