Abstrakt | Secure computation enables multiple mutually distrusting parties to jointly evaluate functions on their private inputs without revealing anything but the result. Generic secure computation protocols in the semi-honest model have been studied extensively and several best practices have evolved. In this work, we design and implement a mixed-protocol framework, called ABY, that efficiently combines secure computation schemes based on Arithmetic sharing, Boolean sharing, and Yao’s garbled circuits and that makes available best practice solutions in secure two-party computation. Our framework allows to pre-compute almost all cryptographic operations and provides novel highly efficient conversions between secure computation schemes based on pre-computed oblivious transfer extensions. ABY supports several standard operations and we perform benchmarks on a local network and in a public intercontinental cloud. From our benchmarks we deduce new insights on the efficient design of secure computation protocols, most prominently that oblivious transfer-based multiplications are much more efficient than using homomorphic encryption. We use our framework to construct mixed-protocols for three example applications, private set intersection, biometric matching, and modular exponentiation, and show that they are much more efficient than using a single protocol. |
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