Advertisement

A Parallel Multi-keyword Top-k Search Scheme over Encrypted Cloud Data

  • Maohu Yang
  • Hua DaiEmail author
  • Jingjing Bao
  • Xun Yi
  • Geng Yang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11783)

Abstract

With searchable encryptions in the cloud computing, users can outsource their sensitive data in ciphertext to the cloud that provides efficient and privacy-preserving multi-keyword top-k searches. However, most existing top-k search schemes over encrypted cloud data are the centralize schemes which are limited in large scale data environment. To support scalable searches, we propose a parallel multi-keyword top-k search scheme over encrypted cloud data. In this scheme, the fragment-based encrypted inverted index is designed, which is indistinguishable and can be used for parallel searching. On the basis of such indexes, a Map-Reduce-based distributed computing framework is adopted to implement the parallel multi-keyword top-k search algorithms. Security analysis and experiment evaluation show that the proposed scheme is privacy-preserving, efficient and scalable.

Keywords

Cloud computing Inverted index Multi-keywords top-k search Parallel computing Searchable encryption 

References

  1. 1.
    González, L.M.V., Rodero-Merino, L., Caceres, J., Lindner, M.A.: A break in the clouds: towards a cloud definition. Comput. Commun. Rev. 39(1), 50–55 (2008)CrossRefGoogle Scholar
  2. 2.
    Kamara, S., Lauter, K.: Cryptographic cloud storage. In: Sion, R., et al. (eds.) FC 2010. LNCS, vol. 6054, pp. 136–149. Springer, Heidelberg (2010).  https://doi.org/10.1007/978-3-642-14992-4_13CrossRefGoogle Scholar
  3. 3.
    Song, D.X., Wagner, D.A., Perrig, A.: Practical techniques for searches on encrypted data. In: 2000 IEEE Symposium on Security and Privacy, Berkeley, California, USA, pp. 44–55, May 2000Google Scholar
  4. 4.
    Goh, E.: Secure indexes. IACR Cryptology ePrint Archive, vol. 2003, p. 216 (2003)Google Scholar
  5. 5.
    Curtmola, R., Garay, J.A., Kamara, S., Ostrovsky, R. : Searchable symmetric encryption: improved definitions and efficient constructions. In: Proceedings of the 13th ACM Conference on Computer and Communications Security, CCS 2006, Alexandria, VA, USA, pp. 79–88 (2006)Google Scholar
  6. 6.
    Cao, N., Wang, C., Li, M., Ren, K., Lou, W.: Privacy-preserving multi-keyword ranked search over encrypted cloud data. In: 30th IEEE International Conference on Computer Communications, Joint Conference of the IEEE Computer and Communications Societies, INFOCOM 2011, pp. 829–837, April 2011Google Scholar
  7. 7.
    Sun, W., Wang, B., Cao, N., Li, M., Lou, W.: Verifiable privacy-preserving multi-keyword text search in the cloud supporting similarity-based ranking. IEEE Trans. Parallel Distrib. Syst. 25(11), 3025–3035 (2014)CrossRefGoogle Scholar
  8. 8.
    Xia, Z., Wang, X., Sun, X., Wang, Q.: A secure and dynamic multi-keyword ranked search scheme over encrypted cloud data. IEEE Trans. Parallel Distrib. Syst. 27(2), 340–352 (2016)CrossRefGoogle Scholar
  9. 9.
    Jiang, X., Yu, J., Yan, J., Hao, R.: Enabling efficient and verifiable multi-keyword ranked search over encrypted cloud data. Inf. Sci. 403, 22–41 (2017)CrossRefGoogle Scholar
  10. 10.
    Chen, C., Zhu, X., Shen, P., Hu, J., Guo, S.: An efficient privacy-preserving ranked keyword search method. IEEE Trans. Parallel Distrib. Syst. 27(4), 951–963 (2016)CrossRefGoogle Scholar
  11. 11.
    Zhu, X., Dai, H., Yi, X., Yang, G., Li, X.: MUSE: an efficient and accurate verifiable privacy-preserving multikeyword text search over encrypted cloud data. Secur. Commun. Netw. 2017, 1 923 476:1–1 923 476:17 (2017)CrossRefGoogle Scholar
  12. 12.
    Fu, Z., Wu, X., Guan, C., Sun, X., Ren, K.: Toward efficient multi-keyword fuzzy search over encrypted outsourced data with accuracy improvement. IEEE Trans. Inf. Forensics Secur. 11(12), 2706–2716 (2016)CrossRefGoogle Scholar
  13. 13.
    Ge, X., Yu, J., Hu, C., Zhang, H., Hao, R.: Enabling efficient verifiable fuzzy keyword search over encrypted data in cloud computing. IEEE Access 6, 45 725–45 739 (2018)CrossRefGoogle Scholar
  14. 14.
    Guo, C., Zhuang, R., Chang, C., Yuan, Q.: Dynamic multi-keyword ranked search based on bloom filter over encrypted cloud data. IEEE Access 7, 35 826–35 837 (2019)CrossRefGoogle Scholar
  15. 15.
    Sun, W., et al.: Privacy-preserving multi-keyword text search in the cloud supporting similarity-based ranking. In: 8th ACM Symposium on Information, Computer and Communications Security, ASIA CCS 2013, Hangzhou, China, pp. 71–82, May 2013Google Scholar
  16. 16.
    Yang, Y., Zhan, Y., Liu, J., Liu, X., Yuan, F., Zhong, S.: Chinese multi-keyword fuzzy rank search over encrypted cloud data based on locality-sensitive hashing. J. Inf. Sci. Eng. 35(1), 137–158 (2019)Google Scholar
  17. 17.
    Zhang, R., Xue, R., Yu, T., Liu, L.: Dynamic and efficient private keyword search over inverted index-based encrypted data. ACM Trans. Internet Technol. 16(3), 21:1–21:20 (2016)CrossRefGoogle Scholar
  18. 18.
    Wang, H., Dong, X., Cao, Z.: Secure and efficient encrypted keyword search for multi-user setting in cloud computing. Peer-To-Peer Netw. Appl. 12(1), 32–42 (2019)CrossRefGoogle Scholar
  19. 19.
    B. D: New York times dataset[db/ol] (2018). http://developer.nytimes.com/docs

Copyright information

© IFIP International Federation for Information Processing 2019

Authors and Affiliations

  • Maohu Yang
    • 1
  • Hua Dai
    • 1
    • 2
    Email author
  • Jingjing Bao
    • 1
  • Xun Yi
    • 3
  • Geng Yang
    • 1
    • 2
  1. 1.Nanjing University of Posts and TelecommunicationsNanjingChina
  2. 2.Jiangsu Security and Intelligent Processing Lab of Big DataNanjingChina
  3. 3.Royal Melbourne Institute of Technology UniversityMelbourneAustralia

Personalised recommendations