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Expressive attribute-based keyword search with constant-size ciphertext

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Abstract

Prior to outsourcing sensitive data, users need to encrypt the data and outsource the ciphertexts to cloud servers. Therefore, efficient search techniques on encrypted data are required. Attribute-based keyword search (ABKS) is a public key encryption with keyword search scheme where a legal user can authorize a proxy to test whether a ciphertext includes some exact keywords without exposing the content of sensitive data to the proxy. However, the main obstacle to implementing existing ABKS schemes is that the computation cost is very heavy, namely linear with the number of required attributes. In this paper, we propose a new ABKS scheme with following features: (1) It supports AND and NOT gates; (2) the size of the searchable ciphertexts is constant; (3) the size of the trapdoors generated by legal users for the proxy is constant; (4) to encrypt a message, the computation cost is constant; and (5) the computation cost of the test algorithm is constant. To the best of our knowledge, it is the first ABKS which has constant-size ciphertext and supports AND and NOT gates.

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Notes

  1. Notably, in this paper, we mainly consider how to encrypt keywords. To encrypt the files, standard public key encryption schemes can be adopted, such as AES encryption, RSA encryption, etc.

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Acknowledgements

We would like to thank Dr Yu Chen for his valuable suggestions. This paper was partially supported by the National Natural Science Foundation of China (Grant Nos. 61300213, 61672207, 61672295), Six Talents Peak Project of Jiangsu Province (Grant No. 2015-DZXX-020) and Jiangsu Provincial Natural Science Foundation (BK20161511).

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Authors and Affiliations

  1. Jiangsu Provincial Key Laboratory of E-Business, Nanjing University of Finance and Economics, Nanjing, Jiangsu, 210003, China

    Jinguang Han

  2. State Key Laboratory of Information Security, Institute of Information Engineering, Chinese Academy of Sciences, Beijing, 100093, China

    Jinguang Han

  3. College of Information Engineering, Nanjing University of Finance and Economics, Nanjing, Jiangsu, 210013, China

    Ye Yang

  4. Faculty of Information Technology, Monash University, Clayton, VIC, Australia

    Joseph K. Liu

  5. College of Computer and Information, Hohai University, Nanjing, 211100, China

    Jiguo Li

  6. School of Computing, Mathematics and Digital Technology, Manchester Metropolitan University, Manchester, M1 5GD, UK

    Kaitai Liang

  7. Jiangsu Engineering Center of Network Monitoring, Nanjing University of Information Science and Technology, Nanjing, Jiangsu, 210044, China

    Jian Shen

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  1. Jinguang Han
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Correspondence to Jinguang Han.

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Communicated by V. Loia.

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Han, J., Yang, Y., Liu, J.K. et al. Expressive attribute-based keyword search with constant-size ciphertext. Soft Comput 22, 5163–5177 (2018). https://doi.org/10.1007/s00500-017-2701-9

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