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

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International Conference on Security and Privacy in Communication Networks (SecureComm 2014)

Abstract

With searchable encryption, a data user is able to perform meaningful search on encrypted data stored in the public cloud without revealing data privacy. Besides handling simple queries (e.g., keyword queries), complex search functions, such as multi-dimensional (conjunctive) range queries, have also been studied in several approaches to provide search functionalities over multi-dimensional data. However, current works supporting multi-dimensional range queries either only achieve linear search complexity or reveal additional private information to the public cloud. In this paper, we propose a tree-based symmetric-key searchable encryption to support multi-dimensional range queries on encrypted data. Besides protecting data privacy, our proposed scheme is able to achieve faster-than-linear search, query privacy and single-dimensional privacy simultaneously compared to previous solutions. More specifically, we formally define the security of our proposed scheme, prove that it is selectively secure, and demonstrate its faster-than-linear efficiency with experiments over a real-world dataset.

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Notes

  1. 1.

    We name it Elm because it is a tree-based solution and it can enhance users’ privacy for multi-dimensional range queries. For the ease of description, when we mention a scheme is faster-than-linear in the rest of this paper, it indicates that the search complexity of it is faster-than-linear with regard to the number of data records.

  2. 2.

    For the ease of description, we assume each dimension has the same size (i.e., \(T_{k}=T\), for every \(k\in [1,w]\)) in the following algorithms..

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Acknowledgement

We would like to thank the reviewers for providing many useful comments. This work was supported in part by the US National Science Foundation under grant CNS-1218085, NSF of China 61272457, National Project 2012ZX03002003-002, 863 Project 2012AA013102, 111 Project B08038, IRT 1078, FRF K50511010001 and NSF of China 61170251.

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Authors and Affiliations

  1. Department of Computer Science, Utah State University, Logan, USA

    Boyang Wang, Yantian Hou, Ming Li & Haitao Wang

  2. State Key Laboratory of Integrated Services Networks, Xidian University, Xián, China

    Hui Li

  3. State Key Laboratory of Information Security, Chinese Academy of Sciences, Beijing, China

    Fenghua Li

Authors
  1. Boyang Wang
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  3. Ming Li
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Corresponding author

Correspondence to Boyang Wang .

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Editors and Affiliations

  1. CAS, Institute of Information Engineering CAS, Beijing, China

    Jing Tian

  2. Institute of Information Engineering, CAS, Beijing, China

    Jiwu Jing

  3. IBM Thomas J. Watson Research Center, New York, New York, USA

    Mudhakar Srivatsa

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© 2015 Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Wang, B., Hou, Y., Li, M., Wang, H., Li, H., Li, F. (2015). Tree-Based Multi-dimensional Range Search on Encrypted Data with Enhanced Privacy. In: Tian, J., Jing, J., Srivatsa, M. (eds) International Conference on Security and Privacy in Communication Networks. SecureComm 2014. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 152. Springer, Cham. https://doi.org/10.1007/978-3-319-23829-6_26

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  • DOI: https://doi.org/10.1007/978-3-319-23829-6_26

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-319-23829-6

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