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    政大機構典藏 > 資訊學院 > 資訊科學系 > 期刊論文 >  Item 140.119/143308
    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/143308


    Title: Fast keyword search over encrypted data with short ciphertext in clouds
    Authors: 曾一凡
    Tseng, Yi-Fan
    Fan, Chun-I;Liu, Zi-Cheng
    Contributors: 資科系
    Keywords: Public key searchable encryption;Key-policy attribute-based encryption;Anonymous KP-ABE;The standard model;Monotonic access structure
    Date: 2022-11
    Issue Date: 2023-02-06 14:31:13 (UTC+8)
    Abstract: Nowadays, it is convenient for people to store their data on clouds. To protect the privacy, people tend to encrypt their data before uploading them to clouds. Due to the widespread use of cloud services, public key searchable encryption is necessary for users to search the encrypted files efficiently and correctly. However, the existing public key searchable encryption schemes supporting monotonic queries suffer from either infeasibility in keyword testing or inefficiency such as heavy computing cost of testing, large size of ciphertext or trapdoor, and so on. In this work, we first propose a novel and efficient anonymous key-policy attribute-based encryption (KP-ABE). Then by applying Shen et al.’s generic construction to the proposed anonymous KP-ABE, we obtain an efficient and expressive public key searchable encryption, which to the best of our knowledge achieves the best performance in testing among the existing such schemes. Only 2 pairings are needed in testing. By applying our searchable encryption, one is able to expressively and efficiently search their encrypted data on clouds, without leaking the keyword information. Besides, we also implement our scheme and others with Python for comparing the performance. From the implementation results, our scheme owns the best performance on testing, and the size of ciphertexts and trapdoors are smaller than most of the existing schemes.
    Relation: Journal of Information Security and Applications, Vol.70, 103320
    Data Type: article
    DOI 連結: https://doi.org/10.1016/j.jisa.2022.103320
    DOI: 10.1016/j.jisa.2022.103320
    Appears in Collections:[資訊科學系] 期刊論文

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