{"ID":2878197,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2508.19180","arxiv_id":"2508.19180","title":"MDD: a Mask Diffusion Detector to Protect Speaker Verification Systems from Adversarial Perturbations","abstract":"Speaker verification systems are increasingly deployed in security-sensitive applications but remain highly vulnerable to adversarial perturbations. In this work, we propose the Mask Diffusion Detector (MDD), a novel adversarial detection and purification framework based on a \\textit{text-conditioned masked diffusion model}. During training, MDD applies partial masking to Mel-spectrograms and progressively adds noise through a forward diffusion process, simulating the degradation of clean speech features. A reverse process then reconstructs the clean representation conditioned on the input transcription. Unlike prior approaches, MDD does not require adversarial examples or large-scale pretraining. Experimental results show that MDD achieves strong adversarial detection performance and outperforms prior state-of-the-art methods, including both diffusion-based and neural codec-based approaches. Furthermore, MDD effectively purifies adversarially-manipulated speech, restoring speaker verification performance to levels close to those observed under clean conditions. These findings demonstrate the potential of diffusion-based masking strategies for secure and reliable speaker verification systems.","short_abstract":"Speaker verification systems are increasingly deployed in security-sensitive applications but remain highly vulnerable to adversarial perturbations. In this work, we propose the Mask Diffusion Detector (MDD), a novel adversarial detection and purification framework based on a \\textit{text-conditioned masked diffusion m...","url_abs":"https://arxiv.org/abs/2508.19180","url_pdf":"https://arxiv.org/pdf/2508.19180v1","authors":"[\"Yibo Bai\",\"Sizhou Chen\",\"Michele Panariello\",\"Xiao-Lei Zhang\",\"Massimiliano Todisco\",\"Nicholas Evans\"]","published":"2025-08-26T16:33:54Z","proceeding":"eess.AS","tasks":"[\"eess.AS\",\"cs.SD\"]","methods":"[\"Diffusion Model\"]","has_code":false}