Fast range query processing with strong privacy protection for cloud computing

Abstract

Privacy has been the key road block to cloud computing as clouds may not be fully trusted. This paper concerns the problem of privacy preserving range query processing on clouds. Prior schemes are weak in privacy protection as they cannot achieve index indistinguishability, and therefore allow the cloud to statistically estimate the values of data and queries using domain knowledge and history query results. In this paper, we propose the first range query processing scheme that achieves index indistinguishability under the indistinguishability against chosen keyword attack (IND-CKA). Our key idea is to organize indexing elements in a complete binary tree called PBtree, which satisfies structure indistinguishability (i.e., two sets of data items have the same PBtree structure if and only if the two sets have the same number of data items) and node indistinguishability (i.e., the values of PBtree nodes are completely random and have no statistical meaning). We prove that our scheme is secure under the widely adopted IND-CKA security model. We propose two algorithms, namely PBtree traversal width minimization and PBtree traversal depth minimization, to improve query processing efficiency. We prove that the worse case complexity of our query processing algorithm using PBtree is O(|R| log n), where n is the total number of data items and R is the set of data items in the query result. We implemented and evaluated our scheme on a real world data set with 5 million items. For example, for a query whose results contain ten data items, it takes only 0.17 milliseconds.

An effective approach for the protection of privacy text data in the CloudDB

“…Li et al [18] discussed the problem about privacy preserving range query processing on clouds, and presented a fast range query processing scheme by organizing indexing elements in a complete binary tree. Wai et al [28] addressed security issues in a cloud database system, and proposed a secure query processing scheme on relational tables and a set of elementary operators on encrypted data, which allows a wide range of database queries to be processed by the server on encrypted data.…”

Practical Private Range Search in Depth

“…Our constructions with their performance and security characteristics are summarized in Table 1 and discussed in detail throughout the paper. We also quantify the costs of Li et al [50], which is clearly subsumed by our Logarithmic-BRC scheme.…”

“…SSE also provides a rigorous framework for accurately defining leakage for any construction. Unfortunately, the scheme by Li et al [50] relies on weak, obsolete SSE definitions (explained in detail in Section 2.1). Moreover, it unnecessarily introduces false positives and does not support updates.…”

“…Nevertheless, OPE is also deterministic, inheriting the distribution leakage. In addition, it inevitably leaks the ordering of the data.The work closest to ours is by Li et al [50], which follows the notion of Searchable Symmetric Encryption (SSE) [12,13,16,18,41,62]. SSE has been studied extensively for keyword queries.…”

“…Our constructions with their performance and security characteristics are summarized in Table 1 and discussed in detail throughout the paper. We also quantify the costs of Li et al [50], which is clearly subsumed by our Logarithmic-BRC scheme.Logarithmic-SRC-i 1 offers the best trade-off between security and efficiency among all our solutions. It employs a novel directed-acyclic graph (DAG) structure that resembles a tree, and entails an extra round of communication between the owner and the server ("i" in its name stands for interactive).…”