具有完全隐私的最短路径自动化迭代检索方法及设备
By employing privacy-preserving homomorphic computation and matrix encoding strategies, the problems of user privacy leakage and high overhead in shortest path queries are solved, enabling secure and efficient automated iterative retrieval of shortest paths.
CN117675675BActive Publication Date: 2026-07-17WUHAN UNIV
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- WUHAN UNIV
- Filing Date
- 2023-11-22
- Publication Date
- 2026-07-17
AI Technical Summary
Technical Problem
Existing technologies for shortest path queries suffer from issues of user privacy leakage and cloud server resource leakage, and traditional methods result in high computational and communication overhead.
Method used
We employ a privacy-based homomorphic shortest path computation method, using fully encrypted computation and matrix encoding strategies to protect the privacy of user location and cloud server routing data. We also design an automated iterative retrieval method to reduce communication and computational overhead.
Benefits of technology
It achieves complete privacy protection for user location information and cloud server routing data, reduces storage space and communication interaction overhead, and improves system security and usability.
✦ Generated by Eureka AI based on patent content.
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Figure CN117675675B_ABST
Abstract
本发明公开了一种具有完全隐私的最短路径自动化迭代检索方法及设备，包括基于隐私同态最短路径计算方法和最短路径自动化迭代检索方法；所述基于隐私同态最短路径计算方法，提出了最短路径信息的完全密文形式计算策略，实现了用户的位置信息及云服务器上的路由数据完全的隐私保护，提升了系统的安全性。所述一种最短路径自动化迭代检索方法，提出了一种新颖的编码矩阵策略，将数据库的数据项编码为单项式，有效降低存储空间开销，其中云服务器端迭代检索方法，实现了用户可无交互执行检索操作，云服务器可以自动化地执行迭代检索操作，最终将完整最短路径返回给用户，有效降低用户与云服务器之间的通信交互和计算开销，大大提升系统的实用性。
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