Sarus: Privacy-Preserving Multi-Vendor Perception Fusion via Homomorphic Encryption
Cooperative perception enables autonomous vehicles (AVs) to improve situational awareness by aggregating detection outputs from multiple agents and sensing platforms, often via a shared fusion service in multi-vendor deployments. However, sharing such outputs at inference time exposes proprietary model behavior and sensitive environmental information, creating significant privacy and security concerns. In this paper, we present Sarus, a privacy-preserving framework for multi-vendor perception fusion via homomorphic encryption (HE), enabling aggregation without revealing individual vendor outputs. Each vendor encodes detections as compact Gaussian moment vectors over a shared spatial latti...
| Authors | Munawar Hasan, Apostol Vassilev |
|---|---|
| Primary category | cs.CR |
| Published | 21 July 2026 |
| Last updated at source | 21 July 2026 |
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