This work considers fully black-box constructions of PRFs from PRGs, where both the construction and the reduction are required to be black-box, and the number of interactions the reduction makes with the adversary is independent of the number of oracle calls the adversary makes to its underlying function within each interaction.
Abstract
In their seminal work, Goldreich, Goldwasser, and Micali [CRYPTO 1984] constructed a pseudorandom function (PRF) using a black-box access to a pseudorandom generator (PRG). When combined with Levin's domain extension technique, the GGM construction invokes the PRG $\omega(\log n)$ times, where $n$ denotes the input length to the PRG. To this day, no black-box construction achieving fewer calls is known. Recently, Beimel, Malkin, and Mazor [CRYPTO 2024] showed that for a certain family of constructions, which they termed \emph{tree constructions}, the GGM construction is optimal. However, the basic challenge of whether a PRF can be built with just \emph{one invocation} of the PRG still remains open. In this work, we consider fully black-box constructions of PRFs from PRGs, where both the construction and the reduction are required to be black-box, and the number of interactions the reduction makes with the adversary is independent of the number of oracle calls the adversary makes to its underlying function within each interaction. Our main result shows that no such construction can have $o(n/\log n)$ and $o(\mathsf{in}/\log\mathsf{in})$ \emph{non-adaptive} calls to the PRG, where $\mathsf{in}$ is the input length of the PRF. This impossibility holds even for weak PRFs with one-bit output, where the adversary is restricted to making i.i.d. uniformly random queries. In addition, we prove a lower bound for weak PRFs with sufficiently long outputs that holds even when the construction is allowed to make adaptive queries to the PRG.
It is shown that non-trivial PoS follow from (a) $\mathsf{E}=\mathsf{DTIME[2^{O(n)}]}$ is hard for exponential-size nondeterministic circuits, and (b) collision-resistant hash functions, and (c) SNARGs for $\mathsf{P}$.
We make progress on the question of constructing explicit evaluation places for leakage-resilient Shamir's secret sharing, over composite order fields. Previously, Maji et al. (EUROCRYPT 2024) showed that random evaluation places yield Shamir's secret sharing over the composite order field $\mathbb{F}_{p^d}$ that is statistically secure against physical-bit leakage. Later, Nguyen (EUROCRYPT 2025) established a dichotomy that linear code-based secret-sharing scheme over the field $\mathbb{F}_{p^d}$ is either statistically secure or completely insecure against such leakage. Building upon Nguyen's dichotomy, we present a partial derandomization of evaluation places, improving upon the Maji et al. result for a restricted regime of parameters. We replace the random choice of $n$ independent evaluation places by the iterates $x_j = \Phi^j(x_0)$ of a simple fixed rational function $\Phi$, where the initial point $x_0 \in \mathbb{F}_{p^d}^*$ is randomly chosen. The randomness in the evaluation places thus drops from $nd \log p$ bits to $d\log p$ bits. Our construction is valid for the regime $n = O(d/\log_p d)$, and any reconstruction threshold $k \ge 2$; in fact, the scheme attains perfect security (statistical distance exactly zero) against single-block leakage. Our technique is a partial fraction nondegeneracy argument that exploits the distinct poles of the rational iterates.
We present a new generic transformation from weak PRFs computable in depth $d(n) = \Omega(\log n)$ to strong PRFs computable in depth $O(d(n))$. This construction refines the classical tree-based paradigm of GGM by {tapering} the internal state so the per-level depth decreases geometrically. We complement the above with new depth-efficient weak PRF constructions based on various standard assumptions. As a corollary, we obtain new $\mathsf{NC}^1$-computable PRFs from various classical assumptions, resolving several long-standing open problems. Concretely, for the first time, we obtain $\mathsf{NC}^1$-computable PRFs: (1) from the \textbf{Learning With Errors (LWE)} assumption with a polynomial modulus-to-noise ratio, improving upon prior low-depth constructions that required Ring-LWE with super-polynomial ratios [Banerjee-Peikert-Rosen, EUROCRYPT 2012]; (2)from the standard \textbf{Learning Parity with Noise (LPN)} assumption, removing the need for structured LPN variants [Boyle et al., FOCS 2020], [Ding-Jain-Komargodski, STOC 2025]; (3) from the \textbf{Computational Diffie-Hellman (CDH)} assumption; prior works relied on the stronger Decisional Diffie-Hellman (DDH) or generalized Diffie-Hellman (GDH) assumptions [Naor-Reingold, FOCS'97, J. ACM'04].
Youlong Ding, Aayush Jain, Ilan Komargodski· 0 citations