publications

2025

1. Relative-error Unateness Testing

   Xi Chen, Diptaksho Palit, Kabir Peshawaria, William Pires, Rocco A. Servedio, and Yiding Zhang

   2025

   Authors ordered alphabetically

   Abstract arXiv

   The model of relative-error property testing of Boolean functions has been the subject of significant recent research effort. In this paper we consider the problem of relative-error testing an unknown and arbitrary $f: {0,1}^n \to {0,1}$ for the property of being a unate function, i.e. a function that is either monotone non-increasing or monotone non-decreasing in each of the $n$ input variables.

   Our first result is a one-sided non-adaptive algorithm for this problem that makes $\tilde{O}(\log(N)/\epsilon)$ samples and queries, where $N=|f^{-1}(1)|$ is the number of satisfying assignments of the function that is being tested and the value of $N$ is given as an input parameter to the algorithm. Building on this algorithm, we next give a one-sided adaptive algorithm for this problem that does not need to be given the value of $N$ and with high probability makes $\tilde{O}(\log(N)/\epsilon)$ samples and queries.

   We also give lower bounds for both adaptive and non-adaptive two-sided algorithms that are given the value of $N$ up to a constant multiplicative factor. In the non-adaptive case, our lower bounds essentially match the complexity of the algorithm that we provide.

2. Laminate: Succinct SIMD-Friendly Verifiable FHE

   Kabir Peshawaria, Zeyu Liu, Ben Fisch, and Eran Tromer

   2025

   First Author

   Abstract ePrint

   In outsourcing computation to untrusted servers, one can cryptographically ensure privacy using Fully Homomorphic Encryption (FHE) or ensure integrity using Verifiable Computation (VC) such as SNARK proofs. While each is practical for some applications in isolation, efficiently composing FHE and VC into Verifiable Computing on Encrypted Data (VCoED) remains an open problem.

   We introduce Laminate, the first practical method for adding integrity to BGV-style FHE, thereby achieving VCoED. Our approach combines the blind interactive proof framework with a tailored variant of the GKR proof system that avoids committing to intermediate computation states. We further introduce variants employing transcript packing and folding techniques. The resulting encrypted proofs are concretely succinct: 270kB, compared to 1TB in prior work, to evaluate a batch of $B=2^{14}$ instances of size $n=2^{20}$ and depth $d=32$. Asymptotically, the proof size and verifier work is $O(d \log (Bn))$, compared to $\Omega(BN\log n)$ in prior work (for ring dimension $N$).

   Unlike prior schemes, Laminate utilizes the full SIMD capabilities of FHE for both the payload circuit evaluation and proof generation; adds only constant multiplicative depth on top of payload evaluation while performing $\tilde{O}(n)$ FHE operations; eliminates the need for witness reduction; and is field-agnostic. The resulting cost of adding integrity to FHE, compared to assuming honest evaluation, is ${\sim}12\times$ to ${\sim}36\times$ overhead (for deep multiplication-heavy circuits of size $2^{20}$), which is $>500\times$ faster than the state-of-the-art.