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Attaques par reconstruction de données biométriques comportementales à l’aide d’alignements d’embeddings

Abstract : Privacy protection is an ethical and legal duty in Europe.Biometric authentication systems are naturally implicated, as they use embeddings, extracted from biometric data.From a view between industry and academic, this thesis explore the embeddings vulnerabilities for data thieft and spoofing, applied to two behavioural biometries : Voice and handwritten digits.Template reconstruction attacks usually have an access to the encoder that produce the embeddings.We proposed to use an unsupervised statistical alignment to analyze a set of embeddings without access to their encoder, to find their associated digits.By fine-tuning this alignment and using the adapted decoder, we reconstructed the digit drawings to spoof a digit authentication system.Speech reconstruction is more complex, because it contains linguistic information weakly transmetted through the embeddings, so we had to use a voice conversion system to reconstruct voice extracts well enough to spoof a speaker authentication system.We also proposed an inversion attack on a pseudo-anonymisation system, using supervised and unsupervised alignements on the raw and anonymized embeddings, to explore its limits.
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Theses
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https://theses.hal.science/tel-03869619
Contributor : ABES STAR :  Contact
Submitted on : Thursday, November 24, 2022 - 1:04:37 PM
Last modification on : Saturday, December 3, 2022 - 3:17:44 AM

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2022LEMA1026.pdf
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  • HAL Id : tel-03869619, version 1

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Thomas Thebaud. Attaques par reconstruction de données biométriques comportementales à l’aide d’alignements d’embeddings. Cryptographie et sécurité [cs.CR]. Le Mans Université, 2022. Français. ⟨NNT : 2022LEMA1026⟩. ⟨tel-03869619⟩

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