STEP: Detecting Audio Backdoor Attacks via Stability-based Trigger Exposure Profiling
With the widespread deployment of deep-learning-based speech models in security-critical applications, backdoor attacks have emerged as a serious threat: an adversary who poisons a small fraction of training data can implant a hidden trigger that controls the model's output while preserving normal behavior on clean inputs. Existing inference-time defenses are not well suited to the audio domain, as they either rely on trigger over-robustness assumptions that fail on transformation-based and semantic triggers, or depend on properties specific to image or text modalities. In this paper, we propose STEP (Stability-based Trigger Exposure Profiling), a black-box, retraining-free backdoor detec...
| Authors | Kun Wang, Meng Chen, Junhao Wang et al. |
|---|---|
| Primary category | cs.CR |
| Published | 18 March 2026 |
| Last updated at source | 18 March 2026 |
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