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Privacy-Preserving Searchable Encryption Scheme Based on Deep Structured Semantic Model over Cloud Application

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Machine Learning for Cyber Security (ML4CS 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13656))

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Abstract

With the continuous development of cloud computing and storage, searchable encryption as a key technology has attracted wide attention. However, existing statistical-based models face long document feature vectors and can not fully catch the document semantics information. This leads to inefficient and unsatisfactory retrieval results. In this paper, we propose a deep structured semantic model of ranked search over encrypted data (DSRSE) based on a convolutional neural network for the first time. In this scheme, document index vectors and query trapdoors are generated by the convolutional neural network model (CNNM) and encrypted by the secure kNN algorithm. In order to protect documents’ privacy security, we use private cloud servers to train the CNNM distributively. All parameters are updated constantly, and the CNNM is updated regularly. Furthermore, a clustering tree based index structure is proposed. Through inner product of document vectors, semantically similar files are clustered together for building a bottom-up index tree which enhances the retrieval efficiency. Analysis and experiments on real datasets illustrate that our schemes perform well in terms of privacy security, search efficiency and accuracy.

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References

  1. Andola, N., Prakash, S., Yadav, V.K., Venkatesan, S., Verma, S., et al.: A secure searchable encryption scheme for cloud using hash-based indexing. J. Comput. Syst. Sci. 126, 119–137 (2022)

    Article  MathSciNet  MATH  Google Scholar 

  2. Bao, Y., Qiu, W., Cheng, X.: Secure and lightweight fine-grained searchable data sharing for IoT-oriented and cloud-assisted smart healthcare system. IEEE Internet Things J. 9(4), 2513–2526 (2021)

    Article  Google Scholar 

  3. Cao, N., Wang, C., Li, M., Ren, K., Lou, W.: Privacy-preserving multi-keyword ranked search over encrypted cloud data. IEEE Trans. Parallel Distrib. Syst. 25(1), 222–233 (2013)

    Article  Google Scholar 

  4. Chen, C., Zhu, X., Shen, P., Guo, S., Tari, Z., Zomaya, A.Y.: An efficient privacy-preserving ranked keyword search method. IEEE Trans. Parallel Distrib. Syst. 27(4), 951–963 (2015)

    Article  Google Scholar 

  5. Chuah, M., Hu, W.: Privacy-aware bedtree based solution for fuzzy multi-keyword search over encrypted data. In: 2011 31st International Conference on Distributed Computing Systems Workshops, pp. 273–281. IEEE (2011)

    Google Scholar 

  6. Dean, J., Corrado, G.S., Monga, R., Chen, K., Ng, A.Y.: Large scale distributed deep networks. Adv. Neural Inf. Process. Syst. 25 (2012)

    Google Scholar 

  7. Deng, C., Yang, E., Liu, T., Li, J., Liu, W., Tao, D.: Unsupervised semantic-preserving adversarial hashing for image search. IEEE Trans. Image Process. 28(8), 4032–4044 (2019)

    Article  MathSciNet  MATH  Google Scholar 

  8. Devlin, J., Chang, M.W., Lee, K., Toutanova, K.: BERT: pre-training of deep bidirectional transformers for language understanding. ar**v preprint ar**v:1810.04805 (2018)

  9. Fu, Z., Ren, K., Shu, J., Sun, X., Huang, F.: Enabling personalized search over encrypted outsourced data with efficiency improvement. IEEE Trans. Parallel Distrib. Syst. 27(9), 2546–2559 (2015)

    Article  Google Scholar 

  10. Fu, Z., Wang, Y., Sun, X., Zhang, X.: Semantic and secure search over encrypted outsourcing cloud based on BERT. Front. Comput. Sci. 16(2), 1–8 (2022). https://doi.org/10.1007/s11704-021-0277-0

    Article  Google Scholar 

  11. 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)

    Article  Google Scholar 

  12. González-Carvajal, S., Garrido-Merchán, E.C.: Comparing BERT against traditional machine learning text classification. ar**v preprint ar**v:2005.13012 (2020)

  13. He, W., Zhang, Y., Li, Y.: Fast, searchable, symmetric encryption scheme supporting ranked search. Symmetry 14(5), 1029 (2022)

    Article  Google Scholar 

  14. He, X., Deng, L., Chou, W.: Discriminative learning in sequential pattern recognition. IEEE Signal Process. Mag. 25(5), 14–36 (2008)

    Article  Google Scholar 

  15. Hu, Z., Dai, H., Yang, G., Yi, X., Sheng, W.: Semantic-based multi-keyword ranked search schemes over encrypted cloud data. Secur. Commun. Netw. 2022 (2022)

    Google Scholar 

  16. Hua, Y., Zhang, D., Ge, S.: Research progress in the interpretability of deep learning models. J. Cybersecur. 5(3), 1–12 (2020)

    Google Scholar 

  17. Huang, P.S., He, X., Gao, J., Deng, L., Acero, A., Heck, L.: Learning deep structured semantic models for web search using clickthrough data. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 2333–2338 (2013)

    Google Scholar 

  18. Jadhav, N., Nikam, J., Bahekar, S.: Semantic search supporting similarity ranking over encrypted private cloud data. Int. J. Emerg. Eng. Res. Technol. 2(7), 215–219 (2014)

    Google Scholar 

  19. Järvelin, K., Kekäläinen, J.: IR evaluation methods for retrieving highly relevant documents. In: ACM SIGIR Forum, vol. 51, pp. 243–250. ACM, NY (2017)

    Google Scholar 

  20. Li, H., Yang, Y., Luan, T.H., Liang, X., Zhou, L., Shen, X.S.: Enabling fine-grained multi-keyword search supporting classified sub-dictionaries over encrypted cloud data. IEEE Trans. Dependable Secure Comput. 13(3), 312–325 (2015)

    Article  Google Scholar 

  21. Li, J., Yan, H., Zhang, Y.: Efficient identity-based provable multi-copy data possession in multi-cloud storage. IEEE Trans. Cloud Comput. (2019)

    Google Scholar 

  22. Li, X., Long, G., Li, S.: Encrypted medical records search with supporting of fuzzy multi-keyword and relevance ranking. In: Sun, X., Zhang, X., **a, Z., Bertino, E. (eds.) ICAIS 2021. LNCS, vol. 12737, pp. 85–101. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-78612-0_7

    Chapter  Google Scholar 

  23. Liu, G., Guo, J.: Bidirectional LSTM with attention mechanism and convolutional layer for text classification. Neurocomputing 337, 325–338 (2019)

    Article  Google Scholar 

  24. Miao, Y., Ma, J., Liu, X., Weng, J., Li, H., Li, H.: Lightweight fine-grained search over encrypted data in fog computing. IEEE Trans. Serv. Comput. 12(5), 772–785 (2018)

    Article  Google Scholar 

  25. Montavon, G., Orr, G.B., Müller, K.-R. (eds.): Neural Networks: Tricks of the Trade. LNCS, vol. 7700. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-35289-8

    Book  Google Scholar 

  26. Palangi, H., et al.: Deep sentence embedding using long short-term memory networks: analysis and application to information retrieval. IEEE/ACM Trans. Audio Speech Lang. Process. 24(4), 694–707 (2016)

    Article  Google Scholar 

  27. Shen, Y., He, X., Gao, J., Deng, L., Mesnil, G.: A latent semantic model with convolutional-pooling structure for information retrieval. In: Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management, pp. 101–110 (2014)

    Google Scholar 

  28. Siva Kumar, D.V.N., Santhi Thilagam, P.: Searchable encryption approaches: attacks and challenges. Knowl. Inf. Syst. 61(3), 1179–1207 (2018). https://doi.org/10.1007/s10115-018-1309-4

    Article  Google Scholar 

  29. Song, D.X., Wagner, D., Perrig, A.: Practical techniques for searches on encrypted data. In: Proceeding 2000 IEEE Symposium on Security and Privacy. S &P 2000, pp. 44–55. IEEE (2000)

    Google Scholar 

  30. Sousa, S., Kern, R.: How to keep text private? A systematic review of deep learning methods for privacy-preserving natural language processing. Artif. Intell. Rev. 1–66 (2022). https://doi.org/10.1007/s10462-022-10204-6

  31. Tian, P., Guo, C., Choo, K.K.R., Liu, Y., Li, L., Yao, L.: EAFS: an efficient, accurate, and forward secure searchable encryption scheme supporting range search. IEEE Syst. J. (2021)

    Google Scholar 

  32. Wang, C., Cao, N., Ren, K., Lou, W.: Enabling secure and efficient ranked keyword search over outsourced cloud data. IEEE Trans. Parallel Distrib. Syst. 23(8), 1467–1479 (2011)

    Article  Google Scholar 

  33. Wang, C., et al.: Enriching query semantics for code search with reinforcement learning. Neural Netw. 145, 22–32 (2022)

    Article  Google Scholar 

  34. Wang, R., Li, Z., Cao, J., Chen, T.: Chinese text feature extraction and classification based on deep learning. In: Proceedings of the 3rd International Conference on Computer Science and Application Engineering, pp. 1–5 (2019)

    Google Scholar 

  35. Wong, W.K., Cheung, D.W., Kao, B., Mamoulis, N.: Secure kNN computation on encrypted databases. In: Proceedings of the 2009 ACM SIGMOD International Conference on Management of Data, pp. 139–152 (2009)

    Google Scholar 

  36. **a, 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 (2015)

    Article  Google Scholar 

  37. **a, Z., Zhu, Y., Sun, X., Chen, L.: Secure semantic expansion based search over encrypted cloud data supporting similarity ranking. J. Cloud Comput. 3(1), 1–11 (2014)

    Article  Google Scholar 

  38. Yang, G., Guo, J., Han, L., Liu, X., Tian, C.: An improved secure certificateless public-key searchable encryption scheme with multi-trapdoor privacy. Peer-to-Peer Netw. Appl. 15(1), 503–515 (2022). https://doi.org/10.1007/s12083-021-01253-9

    Article  Google Scholar 

  39. Yang, J., Zou, B., Qiu, H., Li, Z.: MLFNet-point cloud semantic segmentation convolution network based on multi-scale feature fusion. IEEE Access 9, 44950–44962 (2021)

    Article  Google Scholar 

  40. Yang, W., Sun, B., Ma, X., Zhu, Y.: A cross-lingual secure semantic searching scheme with semantic analysis on ciphertext. Electron. Lett. 58(3), 103–105 (2022)

    Article  Google Scholar 

  41. Yang, Y., Liu, X., Deng, R.H.: Multi-user multi-keyword rank search over encrypted data in arbitrary language. IEEE Trans. Dependable Secure Comput. 17(2), 320–334 (2017)

    Article  Google Scholar 

  42. Zeng, M., Qian, H.F., Chen, J., Zhang, K.: Forward secure public key encryption with keyword search for outsourced cloud storage. IEEE Trans. Cloud Comput. (2019)

    Google Scholar 

  43. Zhang, L., **ong, H., Huang, Q., Li, J., Choo, K.K.R., Li, J.: Cryptographic solutions for cloud storage: challenges and research opportunities. IEEE Trans. Serv. Comput. (2019)

    Google Scholar 

  44. Zhang, M., Chen, Y., Huang, J.: SE-PPFM: a searchable encryption scheme supporting privacy-preserving fuzzy multikeyword in cloud systems. IEEE Syst. J. 15(2), 2980–2988 (2020)

    Article  Google Scholar 

  45. Zhang, W., Gupta, S., Lian, X., Liu, J.: Staleness-aware Async-SGD for distributed deep learning. ar**v preprint ar**v:1511.05950 (2015)

  46. Zhang, X., Zhao, B., Qin, J., Hou, W., Su, Y., Yang, H.: Practical wildcard searchable encryption with tree-based index. Int. J. Intell. Syst. 36(12), 7475–7499 (2021)

    Article  Google Scholar 

  47. Zhao, S., Zhang, H., Zhang, X., Li, W., Gao, F., Wen, Q.: Forward privacy multikeyword ranked search over encrypted database. Int. J. Intell. Syst. (2022)

    Google Scholar 

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Acknowledgments

This work was supported by the National Natural Science Foundation of China under Grant Numbers: 62001055, 62102017, 61932014, 61972018 and the Fundamental Research Funds for the Central Universities (YWF-22-L-1273).

Author information

Authors and Affiliations

  1. School of Cyber Science and Technology, Beihang University, Bei**g, 100191, China

    Na Wang, Shangcheng Zhang, Jianwei Liu, Kaifa Zheng & Jiawen Qiao

  2. School of Artificial Intelligence, Bei**g University of Posts and Telecommunications, Bei**g, 100876, China

    Jian Jiao

  3. School of Cyberspace Security, Bei**g University of Posts and Telecommunications, Bei**g, 100876, China

    Junsong Fu

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  1. Na Wang
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Corresponding author

Correspondence to Junsong Fu .

Editor information

Editors and Affiliations

  1. School of Computing and Informatics, University of Louisiana at Lafayette, Lafayette, IN, USA

    Yuan Xu

  2. Institute of Artificial Intelligence and Blockchain, Guangzhou University, Guangzhou, China

    Hongyang Yan

  3. Institute of Artificial Intelligence and Blockchain, Guangzhou University, Guangzhou, China

    Huang Teng

  4. Guangdong Polytechnic Normal University, Guangzhou, China

    Jun Cai

  5. Institute of Artificial Intelligence and Blockchain, Guangzhou University, Guangzhou, China

    ** Li

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Wang, N. et al. (2023). Privacy-Preserving Searchable Encryption Scheme Based on Deep Structured Semantic Model over Cloud Application. In: Xu, Y., Yan, H., Teng, H., Cai, J., Li, J. (eds) Machine Learning for Cyber Security. ML4CS 2022. Lecture Notes in Computer Science, vol 13656. Springer, Cham. https://doi.org/10.1007/978-3-031-20099-1_49

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  • DOI: https://doi.org/10.1007/978-3-031-20099-1_49

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