Preprocessing Failure and Adversarial Detection in Depthwise-Separable Edge Vision Systems
Preprocessing-based defenses are the standard first-line response to adversarial attacks on edge vision systems, requiring no retraining, no architectural changes, and widely recommended as model-agnostic mitigations. Yet the foundational evaluations of these defenses were conducted on residual or Inception-class architectures, not on the depthwise-separable CNNs that dominate edge deployments. This untested assumption leaves a gap in the security evaluation literature. This paper closes that gap by evaluating six preprocessing defenses against adversarial perturbations across both architecture families. Across all perturbation levels and defenses tested, the two depthwise-separable archi...
| Authors | Jannatul Masruk Mukta, Rifa Sanjida, Adrita Rahman Tory et al. |
|---|---|
| Primary category | cs.CV |
| Published | 3 September 2026 |
| Last updated at source | 3 September 2026 |
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