Tree-Based Multi-dimensional Range Search on Encrypted Data with Enhanced Privacy

Wang, Boyang; Hou, Y. Thomas; Li, Ming; Wang, Haitao; Li, Hui; Li, Fenghua

doi:10.1007/978-3-319-23829-6_26

Cited by 27 publications

(42 citation statements)

References 27 publications

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“…He extended the original scheme to support multi-dimensional range queries by replacing B+ trees with kd-trees in the implementation. Wang et al [8] presented a scheme for evaluating multi-dimensional range queries by using asymmetric scalar-product preserving encryption and R-trees. However, these two methods lead to single-dimensional privacy leakage.…”

Section: A Secure Range Querymentioning

confidence: 99%

Multi-dimensional Range Query on Outsourced Database with Strong Privacy Guarantee

Giang¹,

Ng²

2017

IJCNIS

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Abstract-Cloud services have provided important solutions for drastically reducing the cost of data management and maintenance. However, data outsourcing not only deprives clients of direct control over their data but also allows the server to gain direct access to the client data. Data encryption has been recognized as the solution to the privacy issue, but it also creates new challenges for both industry and academia. A naive question is whether the client still has the capability to query and obtain useful information when the data are encrypted and stored remotely. This paper investigates a solution to one of the most important types of query operations over encrypted data, namely multidimensional range queries. Our solution combines cryptographic techniques with the bucketization approach. We leverage a three-party architecture and secure multiparty computation to design and analyze the security of the protocols. Further, we discuss solutions for both static and dynamic datasets where new data records can be appended. First, we present the solutions for the case when the set of attributes in the query is pre-defined. Subsequently, we discuss the generalization.

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Section: A Secure Range Querymentioning

confidence: 99%

Multi-dimensional Range Query on Outsourced Database with Strong Privacy Guarantee

Giang¹,

Ng²

2017

IJCNIS

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“…In more detail, this kind of encryption has the following characteristic: given two plaintexts x and y with property x ≥ y, the same property Enc(x) ≥ Enc(y) holds for their corresponding ciphertexts. A first concrete implementation of order-preserving encryption was introduced by Scheme Sublinear Index Leakage Search Time Boneh, Waters [6] no n/a Shi et al [28] no n/a Shen et al [27] no n/a Lu [23] yes Order Wang et al [30] yes Bucketization Wang et al [31] yes Distance Demertzis et al [10] yes -This paper yes - Boldyreva et al in [4] and optimized in [21]. However, privacy properties of such encryption schemes might be questionable for highly sensitive data.…”

Section: Related Workmentioning

confidence: 99%

“…A trade-off between privacy and performance for range queries is proposed in [15] by using bucketization of indexed ciphertexts. Other tree index approaches have been published by Wang et al in [30], however, again bucketization of indexed ciphertexts is leaked. In [31] an encryption is used that leaks the relative distance of all indexed ciphertexts to build an R-tree as index for ciphertexts.…”

Section: Related Workmentioning

confidence: 99%

Poly-Logarithmic Range Queries on Encrypted Data with Small Leakage

Hahn

Kerschbaum

2016

Proceedings of the 2016 ACM on Cloud Computing Security Workshop

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Privacy-preserving range queries allow encrypting data while still enabling queries on ciphertexts if their corresponding plaintexts fall within a requested range. This provides a data owner the possibility to outsource data collections to a cloud service provider without sacrificing privacy nor losing functionality of filtering this data. However, existing methods for range queries either leak additional information (like the ordering of the complete data set) or slow down the search process tremendously by requiring to query each ciphertext in the data collection. We present a novel scheme that only leaks the access pattern while supporting amortized polylogarithmic search time. Our construction is based on the novel idea of enabling the cloud service provider to compare requested range queries. By doing so, the cloud service provider can use the access pattern to speed-up search time for range queries in the future. On the one hand, values that have fallen within a queried range, are stored in an interactively built index for future requests. On the other hand, values that have not been queried do not leak any information to the cloud service provider and stay perfectly secure. In order to show its practicability we have implemented our scheme and give a detailed runtime evaluation.

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“…[14]- [17] propose a privacy-preserving multi-keyword text search scheme with similarity-based ranking. However, in [14]- [16], a tree-based index structure is used to improve the search efficiency, and they cannot handle the data updates efficiently: the data owner needs to update the whole search index when inserting or deleting a document. In [17], an additional trusted server is needed to support the index and trapdoor generation.…”

Section: Related Workmentioning

confidence: 99%

Privacy-preserving ranked multi-keyword search leveraging polynomial function in cloud computing

Ren

Chen

Yang

et al. 2014

2014 IEEE Global Communications Conference

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Abstract-The rapid deployment of cloud computing provides users with the ability to outsource their data to public cloud for economic savings and flexibility. To protect data privacy, users have to encrypt the data before outsourcing to the cloud, which makes the data utilization, such as data retrieval, a challenging task. It is thus desirable to enable the search service over encrypted cloud data for supporting effective and efficient data retrieval over a large number of data users and documents in the cloud. Existing approaches on encrypted cloud data search either focus on single keyword search or become inefficient when a large amount of documents are present, and thus have little support for the efficient multi-keyword search. In this paper, we propose a light-weight search approach that supports efficient multi-keyword ranked search in cloud computing system. Specifically, we first propose a basic scheme using polynomial function to hide the encrypted keyword and search patterns for efficient multi-keyword ranked search. To enhance the search privacy, we propose a privacy-preserving scheme which utilizes the secure inner product method for protecting the privacy of the searched multi-keywords. We analyze the privacy guarantee of our proposed scheme and conduct extensive experiments based on the real-world dataset. The experiment results demonstrate that our scheme can enable the encrypted multi-keyword ranked search service with high efficiency in cloud computing.

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Tree-Based Multi-dimensional Range Search on Encrypted Data with Enhanced Privacy

Cited by 27 publications

References 27 publications

Multi-dimensional Range Query on Outsourced Database with Strong Privacy Guarantee

Multi-dimensional Range Query on Outsourced Database with Strong Privacy Guarantee

Poly-Logarithmic Range Queries on Encrypted Data with Small Leakage

Privacy-preserving ranked multi-keyword search leveraging polynomial function in cloud computing

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