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Ciphertext Retrieval Technology of Homomorphic Encryption Based on Cloud Pretreatment

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10638))

Abstract

Ciphertext retrieval in cloud computing environments requires both security and retrieval efficiency. This paper proposes a Ciphertext Retrieval based on Cloud Pretreatment (CRBCP) based on cloud preprocessing. The scheme divides the cloud into the file server and the index server. Firstly, the program uploads the ciphertext document set to the file server and index server. A lot of preprocessing work is done in the index server and generate an inverted index table. Then, the program uploads the ciphertext retrieval item to the index server. Term Frequency-Inverse Document Frequency (TF-IDF) is used the to get the weight vector of the ciphertext document and the ciphertext retrieval item. Finally, the index server calculates the similarity and returns the result to the client. The simulation results show that the efficiency of encryption and decryption time in the algorithm is obviously higher than that of DjikGentryHaleviVaikuntanathan (DGHV) and Based Vector space model and Homomorphism ciphertext retrieval scheme (BVH). The overall efficiency of ciphertext retrieval in the program is superior than others. In the protection of user data privacy and security under the premise, CRBCP scheme preprocesses the ciphertext in the index server. This will not only greatly improve the efficiency of ciphertext retrieval and reduce the computational pressure on the client, but also fully embody the concept and advantages of cloud computing.

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Acknowledgement

This work is supported by the Liaoning Provincial Department of Education Science Fund Project (L2013064), China Aviation Industry Technology Innovation Fund Project (Basic Research) (2013S60109R).

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Correspondence to Changqing Gong .

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Gong, C., Xiao, Y., Li, M., Han, S., Lin, N., Guo, Z. (2017). Ciphertext Retrieval Technology of Homomorphic Encryption Based on Cloud Pretreatment. In: Liu, D., Xie, S., Li, Y., Zhao, D., El-Alfy, ES. (eds) Neural Information Processing. ICONIP 2017. Lecture Notes in Computer Science(), vol 10638. Springer, Cham. https://doi.org/10.1007/978-3-319-70139-4_75

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  • DOI: https://doi.org/10.1007/978-3-319-70139-4_75

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-70138-7

  • Online ISBN: 978-3-319-70139-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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