A Searchable and Verifiable Data Protection Scheme for Scholarly Big Data
Scientific research achievements play a positive role in the promotion of social development. Scholarly big data include scholars’ scientific research, experimental data, and their own identity information. The security of scholarly big data relates to the authors’ reputation and the copyright of their works. This paper proposes a trusted third-party-aided searchable and verifiable data protection scheme that utilizes cloud computing technology. For a better description of the the protocol, we first present a user-differentiated system model and a cube data storage structure. On the basis of the novel system model and data structure, the scheme helps the users review the integrity of their uploaded or downloaded data at any time and search the online scholarly data with encrypted keywords. The security analysis and performance simulation demonstrate that the novel scheme is a secure and efficient scheme for scholarly big data applications.
Cloud data secure searches are among the problems faced by users with the continuous development of cloud computing technology. A large number of researchers , , , ,  have devoted efforts to proposing reliable schemes for secure searches of the data in the cloud. Orencik et al.  present a privacy-preserving searchable scheme for encrypted data using queries with multiple keywords. Additionally, the scheme can hide the search patterns and provide an effective scoring and ranking capability. Focusing on the range query problem, Jho et al.  present a novel searchable encryption protocol that provides an efficient range query by utilizing symmetric key encryption systems. Miao et al.  present a scheme that can achieve a verifiable conjunctive keywords search of encrypted data without a secure channel. The scheme is proved to ensure data integrity and availability.
In this paper can meet the user’s requirements for data integrity verification and keyword encrypted search. A scenario was set up to better demonstrate the workflow and features of the proposed scheme. A user u (author or editor) sends data to CS with a series of encrypted keywords, and another user u ∗ (reader) searches the data for the keyword W∗ and asks the system to provide an integrity verification of the data results for which he is searching. Note that this reader may be the author or editor himself or other people who pass the system authentication. In addition, the proposed scheme allows multiple users to upload data. To simplify the scheme described in this section, only one user is designed to upload data for searching.
In this paper, we construct a system model that can distinguish the users according to their roles and special requirements of scholarly big data. Moreover, an innovative cube data storage structure is proposed. On the basis of the novel system and data structure, we present a novel searchable and verifiable data protection scheme for scholarly big data. The security and performance analyses show that our scheme is efficient for scholarly big data. In the future, we will design a secure data sharing scheme for scholarly big data to supplement our current scheme.
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