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Achieving up to 20X reductions in communication overhead and 10X latency cuts, DFA revolutionizes the efficiency of function secret sharing in privacy-preserving systems.
Choosing the right privacy-preserving ML technique is more than just latency: this benchmark reveals the hidden energy and monetary costs that can make MPC cheaper than FHE in some surprising scenarios.
