Secure Arithmetic Computation with Constant Computational Overhead

We study the complexity of securely evaluating an arithmetic circuit over a finite field $F$ in the setting of secure two-party computation with semi-honest adversaries. In all existing protocols, the number of arithmetic operations per multiplication gate grows either linearly with $\log |F|$ or polylogarithmically with the security parameter. We present the first protocol that only makes a *constant* (amortized) number of field operations per gate. The protocol uses the underlying field $F$ as a black box, and its security is based on arithmetic analogues of well-studied cryptographic assumptions. Our protocol is particularly appealing in the special case of securely evaluating a ``vector-OLE\u27\u27 function of the form $\vec{a}x+\vec{b}$, where $x\in F$ is the input of one party and $\vec{a},\vec{b}\in F^w$ are the inputs of the other party. In this case, which is motivated by natural applications, our protocol can achieve an asymptotic rate of $1/3$ (i.e., the communication is dominated by sending roughly $3w$ elements of $F$). Our implementation of this protocol suggests that it outperforms competing approaches even for relatively small fields $F$ and over fast networks. Our technical approach employs two new ingredients that may be of independent interest. First, we present a general way to combine any linear code that has a fast encoder and a cryptographic (``LPN-style\u27\u27) pseudorandomness property with another linear code that supports fast encoding and *erasure-decoding*, obtaining a code that inherits both the pseudorandomness feature of the former code and the efficiency features of the latter code. Second, we employ local *arithmetic* pseudo-random generators, proposing arithmetic generalizations of boolean candidates that resist all known attacks