On the vulnerability of face verification systems to hill-climbing attacks
By Javier Galbally, C. McCool, Julian Fierrez, Sébastien Marcel, Javier Ortega-Garcia. 2010
148 citations recorded by the source corpus.
Subfields: Computer Vision and Pattern Recognition, Information Systems, Safety, Robustness & Interpretability, Signal Processing
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
- Battista Biggio
- Fabio Roli
- Giorgio Fumera
- Sébastien Marcel
- Gian Luca Marcialis
- André Anjos
- Junichi Yamagishi
- N. Evans
In Information Systems
- Fabio Roli
- Battista Biggio
- Giorgio Fumera
- Gian Luca Marcialis
- Sébastien Marcel
- Zahid Akhtar
- N. Evans
- André Anjos
In Safety, Robustness & Interpretability
- Battista Biggio
- Fabio Roli
- Giorgio Fumera
- Gian Luca Marcialis
- Sébastien Marcel
- Nicolas Papernot
- Giorgio Giacinto
- André Anjos
In Signal Processing
- Fabio Roli
- Battista Biggio
- Giorgio Fumera
- Gian Luca Marcialis
- Sébastien Marcel
- N. Evans
- Junichi Yamagishi
- Haizhou Li
Citations in the corpus
- Accessorize to a Crime: Real and Stealthy Attacks on State-of-the-Art Face Recognition (2016, background): “Other work showed how to compromise the privacy of users enrolled in FRSs [11, 12].”
- Security evaluation of biometric authentication systems under real spoofing attacks (2012, background): “Besides the so-called “indirect attacks”, which require some knowledge of the system or access to its internal parameters [32, 1, 13, 24], much more attention has been devoted to the so-called “direct attacks”, namely, attacks which consist of submitting a counterfeited biometric (i.”
- Pattern Recognition Systems under Attack: Design Issues and Research Challenges (2014, background): “However, the presence of intelligent, adaptive adversaries who exploit their knowledge of the targeted system to evolve their attack strategy over time, introduces a further source of adversarial non-stationarity, that can be modeled by introducing a random variable A, as p(X,Y,A; t)[41, 20] (see…”
- Counter-measures to photo attacks in face recognition: A public database and a baseline (2011, background): “In this work we are particularly concerned with direct [2] print-attacks to unimodal 2-D (visual spectra) face-recognition systems(1).”
- Spoofing and countermeasures for speaker verification: A survey (2015, background): “A generic biometric system may be manipulated or attacked at various stages between sample acquisition and the delivery of an authentication result (Ratha et al., 2001; Faundez-Zanuy, 2004; Galbally et al., 2010).”
- Motion-based counter-measures to photo attacks in face recognition (2014, background): “In this work we are particularly concerned with direct attacks [4] to unimodal 2D (visual spectra) face-recognition systems1.”