Quantum Fast Implementation of Functional Bootstrapping and Private Information Retrieval
AI Breakdown
Get a structured breakdown of this paper — what it's about, the core idea, and key takeaways for the field.
Abstract
Classical privacy-preserving computation techniques safeguard sensitive data in cloud computing, but often suffer from low computational efficiency. In this paper, we show that employing a single quantum server can significantly enhance both the efficiency and security of privacy-preserving computation. We propose an efficient quantum algorithm for functional bootstrapping of large-precision plaintexts, reducing the time complexity from exponential to polynomial in plaintext-size compared to classical algorithms. To support general functional bootstrapping, we design a fast quantum private information retrieval (PIR) protocol with logarithmic query time. The security relies on the learning with errors (LWE) problem with polynomial modulus, providing stronger security than classical ``exponentially fast'' PIR protocol based on ring-LWE with super-polynomial modulus. Technically, we extend a key classical homomorphic operation, known as blind rotation, to the quantum setting through encrypted conditional rotation. Underlying our extension are insights for the quantum extension of polynomial-based cryptographic tools that may gain dramatic speedups.