Practical quantum computing on encrypted data

TL;DR

This paper presents a practical quantum computing method on encrypted data using continuous variables, demonstrating unconditional security and real-world feasibility for privacy-preserving cloud computing.

Contribution

It introduces a quantum approach for secure computation on encrypted data with experimental validation using Gaussian operations, advancing practical quantum privacy solutions.

Findings

Achieved secure quantum computation over 10 km distances

Demonstrated experimental implementation with Gaussian displacement and squeezing

Showed potential for widespread adoption in cloud-based quantum networks

Abstract

The ability to perform computations on encrypted data is a powerful tool for protecting a client's privacy, especially in today's era of cloud and distributed computing. In terms of privacy, the best solutions that classical techniques can achieve are unfortunately not unconditionally secure in the sense that they are dependent on a hacker's computational power. Here we theoretically investigate, and experimentally demonstrate with Gaussian displacement and squeezing operations, a quantum solution that achieves the unconditional security of a user's privacy using the practical technology of continuous variables. We demonstrate losses of up to 10 km both ways between the client and the server and show that security can still be achieved. Our approach offers a number of practical benefits, which can ultimately allow for the potential widespread adoption of this quantum technology in future cloud-based computing networks.