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Privacy-Preserving Multi-keyword Search over Outsourced Data for Resource-Constrained Devices

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Blockchain and Trustworthy Systems (BlockSys 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1267))

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Abstract

With the rapid development of cloud computing, a variety of cloud-based applications have been developed. Since cloud computing has the features of high capacity and flexible computing, more and more users are motivated to outsource their data to the cloud server for economic savings. Users are able to search over outsourced data according to some keywords with the help of the cloud server. During data searching, the confidentiality of the relevant data could be compromised since the keywords may contain some sensitive information. However, existing privacy-preserving keyword search proposals have high computation complexity, which are not applicable to IoT-related scenarios. That is, the data processing and search trapdoor generation procedures require the users to take resource-intensive computations, e.g., high-dimensional matrix operations, which are unaffordable by resource-constrained devices. To address this issue, we propose a light-weight privacy-preserving multi-keyword search scheme. The security and performance analyses demonstrate that our scheme outperforms existing solutions and is practical in applications.

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Acknowledgements

This article is supported in part by the National Natural Science Foundation of China under projects 61862012, 61772150, 61862011, 61962012 and 61902123, the Guangxi Key R&D Program under project AB17195025, the Guangxi Natural Science Foundation under grants 2018GXNSFDA281054, 2018GXNSFAA281232, 2019GXNSFFA245015, 2019GXNSFGA245004 and AD19245048, the Peng Cheng Laboratory Project of Guangdong Province PCL2018KP004, the China Postdoctoral Science Foundation under Project 2019M662769, and the Natural Science Foundation of Hunan Province under Project 2020JJ5085.

Author information

Authors and Affiliations

  1. Guangxi Key Laboratory of Cryptography and Information Security, School of Computer Science and Information Security, Guilin University of Electronic Technology, Guilin, 541004, China

    Lin-Gang Liu, Yong Ding & Yujue Wang

  2. School of Mechanical and Electrical Engineering, Guilin University of Electronic Technology, Guilin, 541004, China

    Meng Zhao

  3. College of Computer Science and Electronic Engineering, Hunan University, Changsha, 410082, China

    Hua Deng

  4. School of Mathematics and Computing Science, Guilin University of Electronic Technology, Guilin, 541004, China

    Huiyong Wang

  5. Cyberspace Security Research Center, Peng Cheng Laboratory, Shenzhen, 518055, China

    Yong Ding

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  1. Lin-Gang Liu
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  3. Yong Ding
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  4. Yujue Wang
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  5. Hua Deng
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Correspondence to Yong Ding .

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Editors and Affiliations

  1. Sun Yat-sen University, Guangzhou, China

    Zibin Zheng

  2. Macau University of Science and Technology, Macau, China

    Hong-Ning Dai

  3. Kunming University of Science and Technology, Kunming, China

    Xiaodong Fu

  4. Dali University, Dali, China

    Benhui Chen

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Liu, LG., Zhao, M., Ding, Y., Wang, Y., Deng, H., Wang, H. (2020). Privacy-Preserving Multi-keyword Search over Outsourced Data for Resource-Constrained Devices. In: Zheng, Z., Dai, HN., Fu, X., Chen, B. (eds) Blockchain and Trustworthy Systems. BlockSys 2020. Communications in Computer and Information Science, vol 1267. Springer, Singapore. https://doi.org/10.1007/978-981-15-9213-3_22

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  • DOI: https://doi.org/10.1007/978-981-15-9213-3_22

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-9212-6

  • Online ISBN: 978-981-15-9213-3

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