Keystroke Dynamics based User Authentication using Deep Learning Neural Networks-Reference-Cited by-同舟云学术

Keystroke Dynamics based User Authentication using Deep Learning Neural Networks

Published:2022-09 Issue: Volume: Page:
ISSN:
Container-title:2022 International Conference on Cyberworlds (CW)
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Author:

Piugie Yris Brice Wandji¹,Di Manno Joel¹,Rosenberger Christophe²,Charrier Christophe²

Affiliation:

1. FIME EMEA,Caen,France,14000

2. Normandie Univ,UNICAEN, ENSICAEN, CNRS, GREYC,Caen,France,14000

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9937199/9937218/09937372.pdf?arnumber=9937372

Reference33 articles.

1. Public keystroke dynamics datasets;monaco,2018

2. A survey on keystroke dynamics biometrics: approaches, advances, and evaluations;zhong;Recent Advances in User Authentication Using Keystroke Dynamics Biometrics,2015

3. Towards a secured authentication based on an online double serial adaptive mechanism of users’ keystroke dynamics;mhenni;International Conference on Digital Society and eGovernments (ICDS),2018

4. Group Leakage Overestimates Performance: A Case Study in Keystroke Dynamics

5. Continuous authentication by free-text keystroke based on CNN and RNN

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