*18:17*[Pub][ePrint] Garbling XOR Gates ``For Free\'\' in the Standard Model, by Benny Applebaum

Yao\'s Garbled Circuit (GC) technique is a powerful cryptographic tool which allows to ``encrypt\'\' a circuit $C$ by another circuit $\\hC$ in a way that hides all information except for the final output. Yao\'s original construction incurs a constant overhead in both computation and communication per gate of the circuit $C$ (proportional to the complexity of symmetric encryption). Kolesnikov and Schneider (ICALP 2008) introduced an optimized variant that garbles XOR gates ``for free\'\' in a way that involves no cryptographic operations and no communication. This variant has become very popular and has been employed in several practical implementations leading to notable performance improvements.

The security of the free-XOR optimization was originally proven in the random oracle model. In the same paper, Kolesnikov and Schneider also addressed the question of replacing the random oracle with a standard cryptographic assumption and suggested to use a hash function which achieves some form of security under correlated inputs. This claim was revisited by Choi et al. (TCC 2012) who showed that a stronger form of security is required, and proved that the free-XOR optimization can be realized based on a new primitive called \\emph{circular 2-correlation hash function}. Unfortunately, it is currently unknown how to implement this primitive based on standard assumptions, and so the feasibility of realizing the free-XOR optimization in the standard model remains an open question.

We resolve this question by showing that the free-XOR approach can be realized in the standard model under the \\emph{learning parity with noise} (LPN) assumption. Our result is obtained in two steps: (1) We show that the hash function can be replaced with a symmetric encryption which remains secure under a combined form of related-key and key-dependent attacks; and (2) We show that such a symmetric encryption can be constructed based on the LPN assumption.