Paper 2017/369

Enforcing Input Correctness via Certification in Garbled Circuit Evaluation

Yihua Zhang, Marina Blanton, and Fattaneh Bayatbabolghani

Abstract

Secure multi-party computation allows a number of participants to securely evaluate a function on their private inputs and has a growing number of applications. Two standard adversarial models that treat the participants as semi-honest or malicious, respectively, are normally considered for showing security of constructions in this framework. In this work, we go beyond the standard security model in the presence of malicious participants and treat the problem of enforcing correct inputs to be entered into the computation. We achieve this by having a certification authority certify user's information, which is consequently used in secure two-party computation based on garbled circuit evaluation. The focus of this work on enforcing correctness of garbler's inputs via certification, as prior work already allows one to achieve this goal for circuit evaluator's input. Thus, in this work, we put forward a novel approach for certifying user's input and tying certification to garbler's input used during secure function evaluation based on garbled circuits. Our construction achieves notable performance of adding only one (standard) signature verification and $$ symmetric key/hash operations to the cost of garbled circuit evaluation in the malicious model via cut-and-choose, in which $$ circuits are garbled and $$ is the length of the garbler's input in bits. Security of our construction is rigorously proved in the standard model.