Paper 2026/610

Concrete Estimation of Correctness and IND-CPA-D Security for FHE via Rare Event Simulation

Abstract

By construction, Fully Homomorphic Encryption schemes have probabilistic correctness due to their underlying cryptographic assumptions. The family of Learning With Errors (LWE) problems assumes that a random error term is added during encryption. Statistically, this error grows as homomorphic computation proceeds. While predicting the noise evolution was initially only a correctness issue, recent works have shown a direct link with the security of FHE schemes in the IND-CPA-D model. Here, we present a framework that provides practical guarantees that the probabilities extrapolated from theoretical models satisfy bounds as small as $2^{-128}$. We show how to obtain strong experimental guarantees that the usual Gaussian model for noise is conservative and that a refined model based on Irwin-Hall distribution is valid. This is realized through an algorithm called importance splitting, which we adapt here to the cryptographic setting. We provide a detailed study in the context of TFHE bootstrapping and its variants. We believe our framework can serve as a baseline to be extended to other schemes, thereby ensuring both correctness and security across all FHE schemes.