Tessera: Secure, Near-Line-Rate Weight Streaming for UMA Edge Accelerators
Deploying proprietary Deep Neural Networks (DNNs) on commodity edge devices demands hardware-backed Digital Rights Management (DRM) capable of withstanding both software-level and physical adversaries. In Unified Memory Architecture (UMA) systems, the host CPU and Neural Processing Unit (NPU) share physical DRAM, leaving plaintext model weights directly readable by a compromised OS kernel. Existing defenses fail in this constrained setting: trusted execution environments monopolize scarce memory with permanently reserved regions, while full-memory encryption operates at page granularity. This forces the system to fetch massive 4 KB memory pages for sub-page tensor tiles, severely cripplin...
| Authors | Animan Naskar |
|---|---|
| Primary category | cs.CR |
| Published | 25 April 2026 |
| Last updated at source | 25 April 2026 |
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