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Confusing-Keyword Based Secure Search over Encrypted Cloud Data

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Abstract

As an important way of communication, the wireless network has brought great convenience to people’s life because of its rapid development. It is a hot topic to protect the data of the wireless network stored in the cloud. In order to solve the problem, this paper presents a privacy protection scheme based on confusing keyword. Based on user history retrieval data, the choosing and embedding of confusing keyword can be selectively implemented. Different from adding random values at the end of the vectors which was generated in other schemes, the embedding time of confusing keyword is selected before the generation of vectors in this paper, so as to truly achieve “random” effect and protect user privacy. In order to eliminate the unrelated documents caused by the matching of confusing keyword, this paper proposes a secondary search scheme based on confusing keyword in scheme 2. Through the construction of two trapdoors, two screenings are performed to ensure the accuracy of the data. Experiments based on real data demonstrate the effectiveness of the two schemes in this paper.

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Acknowledgments

This work is supported by the National Natural Science Foundation of China under grant U1836110, 61772283, U1536206, U1405254, 61602253, 61672294, 61502242; by the National Key R&D Program of China under grant 2018YFB1003205; by China Postdoctoral Science Foundation (2017M610574); by The Jiangsu Basic Research Programs-Natural Science Foundation under grant numbers BK20150925 and BK20151530; by the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD) fund; by the Major Program of the National Social Science Fund of China (17ZDA092), Qing Lan Project, Meteorology Soft Sciences Project; by the Collaborative Innovation Center of Atmospheric Environment and Equipment Technology (CICAEET) fund, China.

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Fu, Z., Liu, Y., Sun, X. et al. Confusing-Keyword Based Secure Search over Encrypted Cloud Data. Mobile Netw Appl 25, 125–132 (2020). https://doi.org/10.1007/s11036-018-1195-8

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