Practical Attribute-based Multi-Keyword Ranked Search Scheme in Cloud Computing


When it comes to realizing fine-grained access control over ciphertext in the background of Cloud Computing, attribute-based keyword search (ABKS) has a broad developing prospect that could be utilized in providing search services to users. Nonetheless, the continued development and application of ABKS is hampered by two outstanding issues. To begin, the majority of ABKS schemes are inherently vulnerable to an inside keyword guessing attack (also known as KGA), which poses a significant risk to the scheme's level of security. Second, the existing ABKS schemes concentrate on either a single keyword search or a conjunctive keyword search. These rigid retrieval modes can result in a loss of productivity due to inaccurate positioning of the user's interests and can drastically diminish the user's overall search experience. In this piece, we will construct a dual server model and introduce a server that is only partially trusted. We are the first to put forward an attribute-based multi-keyword ranked search scheme against inside keyword guessing attack (abbreviated as ABKRS-KGA), which allows us to solve both of the aforementioned problems at the same time. This scheme is based on the dual server model and the techniques that we have proposed. In our system, user queries contain weighted keywords, and the files that are returned to the user can be ranked according to the user's interest in the query they submitted. We present stringent security definitions for two distinct categories of adversaries, and we are the first to demonstrate that the construction is adaptively secure against both chosen-keyword attack (CKA) and key generation attack (KGA). In conclusion, an all-side simulation using a data set taken from the real world is carried out for the proposed scheme, and the results of the simulation show that the efficiency of the proposed scheme is satisfactory.

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