Vanessa Nesterowicz

dblp:284/8511 · DBLP profile ↗
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2ranked-venue papers
0as first author
2since 2021 · last 2023
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Security and privacy · 2 · 2 since 2021Artificial intelligence and machine learning · 1 · 1 since 2021Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 since 2021Human-computer interaction and ubiquitous computing · 1 · 1 since 2021
YearPublicationVenuePosition
2023 Multi-Biometric Fuzzy Vault based on Face and Fingerprints
abstract
The fuzzy vault scheme has been established as cryptographic primitive suitable for privacy-preserving biometric authentication. To improve accuracy and privacy protection, biometric information of multiple characteristics can be fused at feature level prior to locking it in a fuzzy vault. In this work, we provide a formalisation of feature-level fusion in multi-biometric fuzzy vaults, on the basis of which relevant security issues are elaborated. In a case study, we construct a multi-biometric fuzzy vault based on face and multiple fingerprints. On a multi-biometric database constructed from the FRGCv2 face and the MCYT-100 fingerprint databases, a perfect recognition accuracy is achieved at a false accept security above 30 bits. We define countermeasures for observed security issues, that are commonly ignored and may impair the overall system’s security. Finally, a method for extending the fuzzy vault scheme with a password is proposed.
Christian Rathgeb, Benjamin Tams, Johannes Merkle, Vanessa Nesterowicz, Ulrike Korte, Matthias Neu
IJCB4
2022 Deep face fuzzy vault: Implementation and performance
Christian Rathgeb, Johannes Merkle, Johanna Scholz, Benjamin Tams, Vanessa Nesterowicz
Comput. Secur.5