Membership Inference Attacks Against Self-supervised Speech Models. (arXiv:2111.05113v3 [cs.CR] UPDATED)

Recently, adapting the idea of self-supervised learning (SSL) on continuous
speech has started gaining attention. SSL models pre-trained on a huge amount
of unlabeled audio can generate general-purpose representations that benefit a
wide variety of speech processing tasks. Despite their ubiquitous deployment,
however, the potential privacy risks of these models have not been well
investigated. In this paper, we present the first privacy analysis on several
SSL speech models using Membership Inference Attacks (MIA) under black-box
access. The experiment results …

attacks speech