Abstract
Searchable public key encryption (SPE) that supports multi-keywords search, allows data users to retrieve encrypted files of interest efficiently, and thus it has been intensively studied during recent years. However, most existing SPE solutions focus on the exact keyword matching, which fails to capture the semantic information of documents. In this paper, we develop a novel SPE scheme supporting semantic multi-keywords search over the encrypted data. Our solution is mainly built on two techniques: one is a shallow neural network model called “word2vec” for capturing the semantic keywords from documents; the other is a keywords conversion method which can convert keywords into a set of vectors. We then utilize an efficient inner product encryption scheme to encrypt these converted vectors and develop the target SPE scheme, which is proven to be secure against chosen keywords attacks. Moreover, we also present both theoretical and experimental analysis to verify the efficiency and accuracy of this scheme. The experiments over a real-world dataset demonstrate that our scheme can obtain a practical performance in terms of time and space complexities. To the best of our knowledge, it is the first time to construct semantic keywords search scheme over encrypted data in the public key setting.
Highlights
With the rapid development of cloud computing and services, more and more enterprises and individuals store their large-scale data on the cloud platforms in order to decrease operation cost
PROPOSED Searchable public key encryption (SPE)-SMKS SCHEME we propose a concrete SPE-SMKS scheme through combining the methods presented in Sec.III to a PO-inner product encryption (IPE) scheme introduced in [26]
The experiment results of the time and space cost of WLH19, ZLW19 and ours are illustrated in Fig. 6 and Fig. 7
Summary
With the rapid development of cloud computing and services, more and more enterprises and individuals store their large-scale data on the cloud platforms in order to decrease operation cost. A straightforward way to solve the this security concern is encrypting sensitive data before outsourcing them. This simple method is very inconvenient for data retrieval. If users want to search files or records satisfying a query condition, they must download all the ciphertext data, decrypt it locally. After these complicated operations, they can perform the query on these plaintext.
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