Figshare
open access
Audio Physical Dynamics Inspired Deepfake Detection for Voice Authentication Systems
Voice authentication systems deployed at the network edge face dual threats: a) sophisticated deepfake synthesis attacks and b) control-plane poisoning in distributed federated learning protocols. We present a framework coupling audio physical dynamics deepfake detection with uncertainty-aware in ed
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- A Training-Free Proactive Defense Against Partial Speech Manipulation via Self-Embedding Steganography#1035602
- Robust Workflow Generation via Adversarial Learning for Audio Deepfake Detection#1033841
- A Federated Deepfake Speech Detection Method Based on Layer-Wise Center-Guided Weighting Aggregation#1156531
- CoReLoop: Parameter-Efficient Controlled Recurrent Refinement for Audio Deepfake Detection#1035647
- Towards Generalizable Deepfake Detection via Real Distribution Bias Correction#1012153
Record · ID 1065662
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive