SENTRY: A Streaming Edge Network Trust Engine for Real-Time Audio Deepfake Detection
Real-time voice cloning has enabled large-scale streaming deepfake and vishing attacks, while existing Network Detection and Response (NDR) solutions rely on GPU-based post-processing that requires buffered audio and generalizes poorly to unseen speech synthesis models. This paper presents SENTRY, a hardware-oriented, streaming trust engine for inline deepfake detection at the network edge. SENTRY employs an integer lifting-wavelet front end together with a bank of multiplier-free transforms, including wavelet-packet envelopes, Walsh-Hadamard sequency profiles, waveform micro-statistics, and long-term spectral features, designed so that acoustic analysis needs only integer add, shift, com...
| Authors | Chirantan Banerjee, Soumita Chatterjee, Bhargab B. Bhattacharya et al. |
|---|---|
| Primary category | cs.SD |
| Published | 17 October 2026 |
| Last updated at source | 17 October 2026 |
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