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Table 2 Examples for primitive switching strategies in hybrid composition of CML frameworks

From: Confidential machine learning on untrusted platforms: a survey

Framework Primitive Switch Operation Switch Justification
Sharma and Chen (2019) SHE → GC Matrix vector multiplication → Sign Check Sign checking is impractically expensive with SHE whereas tolerable with GC.
Nikolaenko et al. (2013) AHE → GC Matrix Additions → Cholesky’s decomposition The operations of division and square root in Cholesky’s decomposition were not feasible with the AHE scheme.
Nikolaenko et al. (2013) AHE → GC Matrix Additions → Gradient Descent Gradient descent involved multiplications, additions, and subtractions not entirely feasible with the AHE scheme.
Mohassel and Zhang (2017) SecSh → GC Matrix-vector multiplication → Comparison Comparison is impossible over randomly shared secrets leading the switch to the garbled circuits.
Mohassel and Zhang (2017) GC → SecSh Comparison → Vector Subtraction Use of garbled circuits for comparison was unavoidable however continuing GC on to vector subtraction would result in excessive cost overhead.
Demmler et al. (2015) SecSh → AHE/OT Data at rest → Multiplication Multiplication with random shares required switching to either AHE or OT protocol involving the two parties in the frameworks.
Riazi et al. (2018) SecSh → GC Matrix matrix multiplication → ReLu computation Sign checking is impossible over randomly shared secrets leading the switch to garbled circuits.
Riazi et al. (2018) GC →SecSh ReLu → Matrix vector multiplication Use of garbled circuits for matrix vector multiplication is impractical.