A Robust Search Method Using Features To Determine Combined Keywords On Cloud Encrypted Data
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Abstract
Users are more comfortable trusting their sensitive information to the cloud as its security continues to improve. However, when there are several encrypted files, each with its own set of keywords for indexing, the storage overhead grows exponentially, and search efficiency suffers. Therefore, this work provides a technique for searching encrypted cloud data that makes use of features to match joint keywords (FMJK). Joint keywords are generated by randomly selecting a subset of the data owner's non-duplicated keywords choice among the documents' extracted keywords; together, these keywords form a keyword dictionary. Every combined keyword matches with a document's feature as well as a query keyword, making the former's result considered a dimension of a document's index with the latter's result considered a dimension about the query trapdoor. Its BM25 method is then utilized for arranging the top k results by the inner product between the document index and the trapdoor.
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