Database outsourcing is a challenge concerning data secrecy. Even if an adversary, including the service provider, accesses the data, she should not be able to learn any information from the accessed data. In this paper, we address this problem for graph-structured data. First, we define a secrecy notion for graph-structured data based on the concepts of indistinguishability and searchable encryption. To address this problem, we propose an approach based on bucketization. Next to bucketization, it makes use of obfuscated indexes and encryption. We show that finding an optimal bucketization tailored to graph-structured data is NP-hard; therefore, we come up with a heuristic. We prove that the proposed bucketization approach fulfills our secrecy notion. In addition, we present a performance model for scale-free networks which consists of (1) a number-of-buckets model that estimates the number of buckets obtained after applying our bucketization approach and (2) a query-cost model. Finally, we demonstrate with a set of experiments the accuracy of our number-of-buckets model and the efficiency of our approach with respect to query processing.

中文翻译：

---

外包图数据查询处理的保密和性能模型

数据库外包是一个涉及数据保密的挑战。即使包括服务提供商在内的对手访问数据，她也不应该能够从访问的数据中获悉任何信息。在本文中，我们针对图结构数据解决了这个问题。首先，我们基于不可区分性和可搜索加密的概念为图结构数据定义了一个保密概念。为了解决这个问题，我们提出了一种基于桶化的方法。除了分桶，它使用混淆索引和加密。我们表明，找到适合图结构数据的最佳分桶是 NP 难的；因此，我们提出了一种启发式方法。我们证明了所提出的桶化方法符合我们的保密理念。此外，我们提出了一个无标度网络的性能模型，它包括（1）一个桶数模型，该模型估计在应用我们的桶化方法后获得的桶数和（2）一个查询成本模型。最后，我们通过一组实验证明了我们的桶数模型的准确性以及我们的方法在查询处理方面的效率。