Secure Equality Test is an important building block in Secure Multi-Party Computation (MPC) with respect to Secure Comparison, also known as Socialist millionaire problem.
A similar question was posted several years ago (Extending the Socialist millionaire problem to three parties), but it seems to be considered from Zero-Knowledge. In this post, I want to discuss this problem from the perspective of Two/Three-Party (2/3PC) Computation.
Definition with respect to 2PC: Given two secret-shared (e.g., additive secret sharing) values $x$ and $y$, held by Alice (i.e., $[x]_1$ and $[y]_1$) and Bob (i.e., $[x]_2$ and $[y]_2$), respectively. After running the secure computation between Alice and Bob, Alice and Bob learn $[z]_1$ and $[z]_2$, respectively, where $z=1$ if $x=y$, otherwise $z=0$. Note that $x$ and $y$ are secret-shared under arithmetic secret sharing while the result bit $z$ is a single bit under boolean sharing.
Recent protocols such as CryptFlow2 and New Primitives for Actively-Secure MPC over Rings with Applications to Private Machine Learning provide secure equality protocols based on 2PC.
So, my questions are:
Is there a protocol for Three Party?
CryptFlow2 is probably the most efficient protocol proposed recently. But there are still too many communications (e.g., the communication round is $logl$ where $l$ is the bit length of the integer, shown in Table 1 in the CryptFlow2 paper).
For me, I'm more concerned with communication overhead. That is, I can accept a bit more computational overhead, but as little communication as possible. So is there any communication-efficient protocol (no matter 2PC or 3PC)?