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Semantic-based Compound Keyword Search over Encrypted Cloud Data | IEEE Journals & Magazine | IEEE Xplore

Semantic-based Compound Keyword Search over Encrypted Cloud Data


Abstract:

Keyword search over encrypted data is essential for accessing outsourced sensitive data in cloud computing. In some circumstances, the keywords that the user searches on ...Show More

Abstract:

Keyword search over encrypted data is essential for accessing outsourced sensitive data in cloud computing. In some circumstances, the keywords that the user searches on are only semantically related to the data rather than via an exact or fuzzy match. Hence, semantic-based keyword search over encrypted cloud data becomes of paramount importance. However, existing schemes usually depend upon a global dictionary, which not only affects the accuracy of search results but also causes inefficiency in data updating. Additionally, although compound keyword search is common in practice, the existing approaches only process them as single words, which split the original semantics and achieve low accuracy. To address these limitations, we initially propose a compound concept semantic similarity (CCSS) calculation method to measure the semantic similarity between compound concepts. Next, by integrating CCSS with Locality-Sensitive Hashing function and the secure kk<; inline-graphic xlink:href="wang-ieq1-2847318.gif"/>-Nearest Neighbor scheme, a semantic-based compound keyword search (SCKS) scheme is proposed. SCKS achieves not only semantic-based search but also multi-keyword search and ranked keyword search. Additionally, SCKS also eliminates the predefined global library and can efficiently support data update. The experimental results on real-world dataset indicate that SCKS introduces low overhead on computation and the search accuracy outperforms the existing schemes.
Published in: IEEE Transactions on Services Computing ( Volume: 14, Issue: 3, 01 May-June 2021)
Page(s): 850 - 863
Date of Publication: 14 June 2018

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