Quantum Searchable Encryption for Cloud Data Based on Full-Blind Quantum Computation
Wenjie Liu, Yinsong Xu, Wen Liu, Haibin Wang, and Zhibin Lei

TL;DR
This paper introduces a quantum searchable encryption scheme for cloud data that leverages a multi-client full-blind quantum computation model, enhancing security and multi-client access in quantum cloud environments.
Contribution
It proposes a novel multi-client full-blind quantum computation model combined with Grover's algorithm for secure quantum searchable encryption in cloud data.
Findings
Resists certain quantum attacks.
Guarantees data and computation blindness.
Supports multi-client encrypted data access.
Abstract
Searchable encryption (SE) is a positive way to protect users sensitive data in cloud computing setting, while preserving search ability on the server side, i.e., it allows the server to search encrypted data without leaking information about the plaintext data. In this paper, a multi-client universal circuit-based full-blind quantum computation (FBQC) model is proposed. In order to meet the requirements of multi-client accessing or computing encrypted cloud data, all clients with limited quantum ability outsource the key generation to a trusted key center and upload their encrypted data to the data center. Considering the feasibility of physical implementation, all quantum gates in the circuit are replaced with the combination of {\pi}/8 rotation operator set {Rz({\pi}/4), Ry({\pi}/4), CRz({\pi}/4), CRy({\pi}/4), CCRz({\pi}/4), CCRy({\pi}/4)}. In addition, the data center is only…
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