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Privacy-Preserving Graph Encryption for Approximate Constrained Shortest Distance Queries

机译:近似约束最短距离查询的隐私保护图加密

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Constrained shortest distance (CSD) queries are a valuable extension of the traditional pairwise shortest distance computation over graph-structured data, where the answers to the queries should fulfill a cost constraint (e.g., the toll payment in road networks). With the popularity of cloud computing, data owners have a strong desire to migrate their privacy-sensitive graphs to remote servers without losing the ability to query them. Existing graph encryption schemes cannot provide security guarantees for CSD queries. In this paper, we present Acro, a graph encryption scheme, which executes approximate CSD queries securely. The homomorphic encryption and the symmetric-key primitives are applied to our scheme. Through a security analysis, we prove that Acro meets the security definition of CQA2-security. The prototype of Acro is implemented and evaluated using real datasets. The results show that our proposal outperforms a state-of-the-art baseline in terms of query accuracy at the cost of enlarging query completion time.
机译:约束最短距离(CSD)查询是对图形结构数据的传统成对最短距离计算的重要扩展,其中查询的答案应满足成本约束(例如,路网中的通行费)。随着云计算的普及,数据所有者强烈希望将其对隐私敏感的图形迁移到远程服务器,而又不会失去查询它们的能力。现有的图形加密方案无法为CSD查询提供安全保证。在本文中,我们提出了一种Acro(一种图加密方案),该方案可以安全地执行近似CSD查询。同态加密和对称密钥原语应用于我们的方案。通过安全性分析,我们证明Acro符合CQA2-security的安全性定义。 Acro的原型是使用实际数据集实现和评估的。结果表明,我们的建议在查询准确性方面优于最新基准,但以增加查询完成时间为代价。

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