SearchaStore: fast and secure searchable cloud services

Abstract

The emergence of Cloud Computing is revolutionizing the way we store, query, analyze and consume data, which also bring forward other development that fundamentally changed our life style. For example, Industry 4.0 and Internet of Things (IoT) can improve the quality of manufacturing and many aspects in our daily life; both of them rely heavily on the cloud computing platform to develop. Central to this paradigm shift is the need to keep any common data, often held at remote outsourced locations and usually to be accessed by different authorized parties, secure from being leaked to unauthorized entities. When using the cloud services, consumer may want to encrypt sensitive data before uploading it to the cloud, but this will also eliminate the possibility to search the data efficiently in the cloud storage. A more practical solution to this is to employ a searchable encryption scheme in the cloud storage, so that user can query the encrypted data efficiently without revealing the sensitive data to the service provider. Besides the security and search features, performance of searchable encryption schemes is also very important when it comes to practical applications. In this paper, we propose several techniques to accelerate the search performance of encrypted data stored on the cloud. Notably, our techniques include massively parallel file encryption, multi-array keyword red black tree (KRBT) implementation, batched keyword search and enhanced parallel search in KRBT. To the best of our knowledge, SearchaStore is the first work that attempts to accelerate searchable encryption using GPU technology.

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References

  1. 1.

    Yang, G., Xie, L., Mantysalo, M., Zhou, X., Walter, S.K., Chen, Q., Zheng, L.: A healthcare information sharing scheme in distributed cloud networks. J. Clust. Comput. 18(4), 1405–1410 (2015)

    Article  Google Scholar 

  2. 2.

    Tao, F., Zuo, Y., Xu, L.D., Zhang, L.: IoT-based intelligent perception and access of manufacturing resource toward cloud manufacturing. IEEE Trans. Ind. Inf. 10(2), 1547–1557 (2014)

    Article  Google Scholar 

  3. 3.

    A. Mhlaba, M. Masinde.: Implementation of Middleware for Internet of Things in Asset Tracking Applications: In-lining Approach. IEEE International Conference on Industrial Informatics, INDIN, pp. 460-469, 2015

  4. 4.

    Mhlaba, A., Masinde, M.: Secure outsourcing of modular exponentiations in cloud and cluster computing. J. Clust. Comput. 19(2), 460–469 (2015)

    Google Scholar 

  5. 5.

    Lee, S.G., Lee, D., Lee, S.: Personalized DTV program recommendation system under a cloud computing environment. IEEE Trans. Consum. Electron. 56(2), 1034–1042 (2010)

    Article  Google Scholar 

  6. 6.

    Kim, Y., Ko, J., Shin, D., Kim, C., Park, C.: A frequency monitoring system development for wide-area power grid protection. J. Clust. Comput. 16(2), 209–219 (2013)

    Article  Google Scholar 

  7. 7.

    Park, S., Park, E., Seo, J., Li, G.: Factors affecting the continuous use of cloud service-focused on security risks. J. Clust. Comput. 19(1), 485–495 (2015)

    Article  Google Scholar 

  8. 8.

    Fang, S., Xu, L., Pei, H., Liu, Y.: An integrated approach to snowmelt flood forecasting in water resource management. IEEE Trans. Ind. Inf. 10(1), 548558 (2014)

    Article  Google Scholar 

  9. 9.

    Xu, L.: Introduction: Systems science in industrial sectors. Syst. Res. Behav. Sci. 30(3), 211213 (2013)

    Article  Google Scholar 

  10. 10.

    Song, X., Wagner, D., Perrig, A.: Practical techniques for searches on encrypted data. SP 00: Proceedings of the IEEE Symposium on Security and Privacy, pp. 44, (2000)

  11. 11.

    Goh, E.J.: Secure indexes. Cryptology ePrint Archive. Report 2003/216. http://eprint.iacr.org/2003/216/

  12. 12.

    Curtmola, R., Garay, J.A., Kamara, S., Ostrovsky, R.: Searchable Symmetric Encryption: Improved Definitions and Efficient Constructions. ACM Conference on Computer and Communications Security, CCS, pp. 7988. (2006)

  13. 13.

    Chase, M., Kamara, S.: Structured Encryption and Controlled Disclosure. ASIACRYPT, Lecture Notes in Computer Science. 6477, pp. 577594. Springer, Heidelberg(2010)

  14. 14.

    Kamara, S., Papamanthou, C., Roeder, T.: Dynamic searchable symmetric encryption. ACM Conference on Computer and Communications Security. pp. 965976. (2012)

  15. 15.

    Naveed, M., Prabhakaran, M., Gunter, C.A.: Dynamic searchable encryption via blind storage. Proceedings of the IEEE Symposium on Security and Privacy, pp. 639–654. (2014)

  16. 16.

    Curtmola, R., Garay, J.A., Kamara, S., Ostrovsky, R.: Searchable symmetric encryption: improved definitions and efficient constructions. J. Comput. Secur. 19(5), 895–934 (2011)

    Article  Google Scholar 

  17. 17.

    Moataz, T., Justus, B., Ray, I., Cuppens-Boulahia, N., Cuppens, F., Ray, I.: Privacy-preserving multiple keyword search on outsourced data in the clouds. Lect. Notes Comput. Sci. 8566(2014), 66–81 (2014)

    Article  Google Scholar 

  18. 18.

    Cash, D., Jarecki, S., Jutla, C.S., Krawczyk, H., Rosu, M., Steiner, M.: Highly-scalable searchable symmetric encryption with support for Boolean queries. Advances in Cryptology. Lecture Notes in Computer Science, vol. 8042, pp. 353–373. Springer, Berlin (2013)

    Google Scholar 

  19. 19.

    Moataz, T., Shikfa, A.: Boolean symmetric searchable encryption. 8th ACM Symposium on Information, Computer and Communications Security, ASIA CCS, pp. 265276. (2013)

  20. 20.

    Yu, J., Lu, P., Zhu, Y., Xue, G., Li, M.: Toward secure multikeyword top-k retrieval over encrypted cloud data. IEEE Trans. Dependable Secur. Comput. 10(4), 239–250 (2013)

    Article  Google Scholar 

  21. 21.

    Kamara, S., Papamanthou, C.: Parallel and Dynamic Searchable Symmetric Encryption. Financial Cryptography, pp. 258–274. Springer, Berlin (2013)

    Google Scholar 

  22. 22.

    Cash, D., Jaeger, J., Jarecki, S., Jutla, C., Krawczyk, H., Rosu, M.C., Steiner, M.: Dynamic Searchable Encryption in Very-Large Databases: Data Structures and Implementation. Network and Distributed System Security Symposium, NDSS (2014)

  23. 23.

    Xia, Z., Wang, X., Sun, X., Wang, Q.: A secure and dynamic multi-keyword ranked search scheme over outsourced cloud data. IEEE Trans. Parallel Distrib.Syst. 27(2), 1–13 (2015)

    Google Scholar 

  24. 24.

    Boneh, D., Kushilevitz, E., Ostrovsky, R., Skeith, W.E. III.: Public key encryption that allows PIR queries. CRYPTO, Lecture Notes in Computer Science. 4622, pp. 5067. Springer, Heidelberg. (2007)

  25. 25.

    Stefanov, E., Shi, E.: ObliviStore: High Performance Oblivious Cloud Storage. Proceedings of the IEEE Symposium on Security and Privacy, pp. 253–267. (2013)

  26. 26.

    Gentry, C., Halevi, S., Smart, N.P.: Fully homomorphic encryption with polylog overhead. Advances in Cryptology—EUROCRYPT, Lecture Notes in Computer Science, vol. 7237, pp. 465–482. Springer, Berlin (2012)

  27. 27.

    Hughes, D.M., Lim, I.S.: Kd-jump: a path-preserving stackless traversal for faster isosurface raytracing on GPUs. IEEE Trans. Vis. Comput. Graph. 15(6), 1555–1562 (2009)

    Article  Google Scholar 

  28. 28.

    Kaczmarski, K.: B+-tree optimized for GPGPU. Lect. Notes Comput. Sci. 7566, 843–854 (2012)

    Article  Google Scholar 

  29. 29.

    C. Kim, J., Chhugani, N., Satish, E., Sedlar, A., Nguyen, D., Kaldewey, T., Lee, V.W., Brandt, S.A., Dubey, P.: FAST: fast architecture sensitive tree search on modern CPUs and GPUs. Proceedings of the 2010 ACM SIGMOD International Conference on Management of data, pp. 339–350. (2010)

  30. 30.

    Chen, X., Ren, L., Wang, Y., Yang, H.: GPU-accelerated sparse LU factorization for circuit simulation with performance modeling. IEEE Trans. Parallel Distrib. Syst. 26(3), 786–795 (2015)

    Article  Google Scholar 

  31. 31.

    Mei, S., He, M., Shen, Z.: Optimizing Hopfield Neural Network for Spectral Mixture Unmixing on GPU Platform. IEEE Geosci. Remote Sens. Lett. 11(4), 818–822 (2014)

    Article  Google Scholar 

  32. 32.

    Hu, L., Nooshabadi, S., Mladenov, T.: Forward error correction with Raptor GF(2) and GF(256) codes on GPU. IEEE Trans. Consum. Electron. 59(1), 273–280 (2013)

    Article  Google Scholar 

  33. 33.

    Lee, W.K., Cheong, H.S., Phan, Raphael C.-W., Goi, B.M.: Fast implementation of block ciphers and PRNGs in Maxwell GPU architecture. J. Clust. Comput. 19(1), 335–347 (2016)

    Article  Google Scholar 

  34. 34.

    Yang, Y., Guan, Z., Sun, H., Chen, Z.: Accelerating RSA with fine-grained parallelism using GPU. Information Security Practice and Experience, Lecture Notes in Computer Science, vol 9065, pp. 454-468. (2015)

  35. 35.

    Park, H., Park, K.: Parallel algorithms for redblack trees. Theor. Comput. Sci. 262(12), 415435 (2001)

    Google Scholar 

  36. 36.

    Enron Dataset. https://www.cs.cmu.edu/enron/. (2015)

Download references

Acknowledgements

This work was supported partially by Universiti Tunku Abdul Rahman Research Fund (UTARRF) under Grant IPSR/RMC/UTARRF/2016-C1/G1.

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Correspondence to Wai-Kong Lee.

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Lee, W., Phan, R.C., Poh, G. et al. SearchaStore: fast and secure searchable cloud services. Cluster Comput 21, 1189–1202 (2018). https://doi.org/10.1007/s10586-017-0941-1

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Keywords

  • Cloud service
  • Secure outsourcing
  • Keyword Red Black Tree
  • Searchable symmetric encryption