Cracking Fuzzy Vaults and Biometric Encryption
By Walter J. Scheirer, Terrance E. Boult. 2007 Biometrics Symposium, 2007
360 citations recorded by the source corpus.
Subfields: Computer Vision and Pattern Recognition, Information Systems, Signal Processing
View Paper: https://www.semanticscholar.org/paper/b4ef98b158f7d98521d38ca56ced0e783e1b2422
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Vision and Pattern Recognition
- Anil K. Jain
- Karthik Nandakumar
- Andreas Uhl
- Christian Rathgeb
- Abhishek Nagar
- K. Plataniotis
- Yongjin Wang
- Arun A. Ross
In Information Systems
- Karthik Nandakumar
- Anil K. Jain
- Christian Rathgeb
- Andreas Uhl
- Abhishek Nagar
- K. Plataniotis
- Yongjin Wang
- Arun A. Ross
In Signal Processing
- Karthik Nandakumar
- Anil K. Jain
- Christian Rathgeb
- Andreas Uhl
- Abhishek Nagar
- K. Plataniotis
- Yongjin Wang
- Arun A. Ross
Citations in the corpus
- A survey on biometric cryptosystems and cancelable biometrics (2011, methodology): “Boult et al. [147,148] proposed cryptographically secure biotokens which they applied to face and fingerprints.”
- Biometric Template Security (2008, background): “There are some specific attacks that can be staged against a fuzzy vault, that is, attacks via record multiplicity, stolen key inversion attack, and blended substitution attack [92].”
- Multibiometric Cryptosystems Based on Feature-Level Fusion (2012, background): “The authentication is deemed successful if is the same as .”
- An Analysis of Random Projection for Changeable and Privacy-Preserving Biometric Verification (2010, background): “Furthermore, the security level of such methods still needs to be further investigated [5], [6].”