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PrivDNN: Partial DNN Encryption for Secure Multi-Party Inference
- Engineer — Learn: Research-stage framework for privacy-preserving ML inference using partial homomorphic encryption; no production deployment target yet, but relevant for teams evaluating MLaaS privacy architectures.
- SOC/IR — Skip
- Leader — Learn: Emerging approach to MLaaS model-and-data confidentiality could inform vendor risk questions around proprietary model exposure; no near-term action required.
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