EVA-S2PMLP proposes secure two-party MLP protocols by splitting inputs into shares and masking matrices, but its base multiplication protocol returns shares whose sum is C_std + A times the masked B, not A times B.
Secureml: A system for scalable privacy- preserving machine learning
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EVA-S2PMLP: Secure and Scalable Two-Party MLP via Spatial Transformation
EVA-S2PMLP proposes secure two-party MLP protocols by splitting inputs into shares and masking matrices, but its base multiplication protocol returns shares whose sum is C_std + A times the masked B, not A times B.