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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. |