Privacy-Preserving PLDA Speaker Verification using Outsourced Secure Computation

Publication date: Available online 1 October 2019Source: Speech CommunicationAuthor(s): Amos Treiber, Andreas Nautsch, Jascha Kolberg, Thomas Schneider, Christoph BuschAbstractThe usage of biometric recognition has become prevalent in various verification processes, ranging from unlocking mobile devices to verifying bank transactions. Automatic speaker verification (ASV) allows an individual to verify its identity towards an online service provider by comparing freshly sampled speech data to reference information stored on the service provider’s server. Due to the sensitive nature of biometric data, the storage and usage thereof is subject to recent EU regulations introduced as means to protect the privacy of individuals enrolled in an automatic biometric verification system. Stored biometric data need to be unlinkable, irreversible, and renewable to satisfy international standards. Preserving privacy in ASV is also important because, contrary to other biometric characteristics such as fingerprints, speech data can be used to infer a lot of sensitive information about the data subject. As a result, some architectures have been proposed to enable privacy-preserving ASV in the encrypted domain. Recently, homomorphic encryption (HE) was proposed to protect both subject features and vendor models in an embedding-based ASV. This architecture improves on previous privacy-preserving ASV by using (probabilistic) embeddings (i-vectors) and by additionally protecting the vendo...

Source: Speech Communication - October 2, 2019 Category: Speech-Language Pathology Source Type: research