Abstract:
Attribute-based keyword search (ABKS) can provide search services and fine-grained access control over ciphertext in cloud computing. Two issues prevent ABKS development and use. First, most ABKS schemes have a built-in keyword guessing attack (KGA), which compromises security.
Second, existing ABKS schemes focus on single or conjunctive keyword search. These inflexible retrieval modes may lead to efficiency loss due to inaccurate positioning of user interest and greatly reduce user search experience.
This project introduces a semi-trusted server and dual server model. Our attribute-based multi-keyword ranked search scheme against inside keyword guessing attack (ABKRS-KGA) solves the two problems simultaneously.
Our system ranks returned files by weighted keywords in user queries. We are the first to prove that the construction is adaptively secure against chosen-keyword attack (CKA) and KGA. Finally, all-side simulation with real-world data set shows that the proposed scheme is efficient.
Note: Please discuss with our team before submitting this abstract to the college. This Abstract or Synopsis varies based on student project requirements.
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