Privacy Attacks Against Biometric Models with Fewer Samples: Incorporating the Output of Multiple Models. (arXiv:2209.11020v1 [cs.CV])

Authentication systems are vulnerable to model inversion attacks where an
adversary is able to approximate the inverse of a target machine learning
model. Biometric models are a prime candidate for this type of attack. This is
because inverting a biometric model allows the attacker to produce a realistic
biometric input to spoof biometric authentication systems.

One of the main constraints in conducting a successful model inversion attack
is the amount of training data required. In this work, we focus on …

arxiv attacks biometric privacy