International Association
for Cryptologic Research

Approximated homomorphic encryption (HE) schemes such as CKKS are commonly used to perform computations over encrypted real numbers. It is commonly assumed that these schemes are not “exact” and thus they cannot execute circuits with unbounded depth over discrete sets, such as binary or integer numbers, without error overflows. These circuits are usually executed using BGV and B/FV for integers and TFHE for binary numbers. This artificial separation can cause users to favor one scheme over another for a given computation, without even exploring other, perhaps better, options. We show that by treating step functions as “clean-up” utilities and by leveraging the SIMD capabilities of CKKS, we can extend the homomorphic encryption toolbox with efficient tools. These tools use CKKS to run unbounded circuits that operate over binary and small-integer elements and even combine these circuits with fixed-point real numbers circuits. We demonstrate the results using the Turing-complete Conway’s Game of Life. In our evaluation, for boards of size 256 $$\times $$ × 256, these tools achieved orders of magnitude faster latency than previous implementations using other HE schemes. We argue and demonstrate that for large enough real-world inputs, performing binary circuits over CKKS, while considering it as an “exact” scheme, results in comparable or even better performance than using other schemes tailored for similar inputs.