Paper 2025/646 Original: eprint.iacr.org/2025/646 ↗

Secret-Key PIR from Random Linear Codes

Abstract

Private information retrieval (PIR) allows to privately read a chosen bit from an $N$-bit database $x$ with $o(N)$ bits of communication. Lin, Mook, and Wichs (STOC 2023) showed that by preprocessing $x$ into an encoded database $\hat x$, it suffices to access only $polylog(N)$ bits of $\hat x$ per query. This requires $|\hat x|\ge N\cdot polylog(N)$, and even larger server circuit size. We consider an alternative preprocessing model (Boyle et al. and Canetti et al., TCC 2017), where the encoding $\hat x$ depends on a client's short secret key. In this secret-key PIR (sk-PIR) model we construct a protocol with $O(N^\epsilon)$ communication, for any constant $\epsilon>0$, from the Learning Parity with Noise assumption in a parameter regime not known to imply public-key encryption. This is evidence against public-key encryption being necessary for sk-PIR. Under a new conjecture related to the hardness of learning a hidden linear subspace of $\mathbb{F}_2^n$ with noise, we construct sk-PIR with similar communication and encoding size $|\hat x|=(1+\epsilon)\cdot N$ in which the server is implemented by a Boolean circuit of size $(4+\epsilon)\cdot N$. This is close to optimal, and the first candidate single-server PIR scheme with linear circuit complexity.