• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

QSDB: An Encrypted Database Model for Privacy-Preserving in Cloud Computing

Vol. 12, No.7, July 31, 2018
10.3837/tiis.2018.07.021, Download Paper (Free):

Abstract

With the advent of database-as-a-service (DAAS) and cloud computing, more and more data owners are motivated to outsource their data to cloud database in consideration of convenience and cost. However, it has become a challenging work to provide security to database as service model in cloud computing, because adversaries may try to gain access to sensitive data, and curious or malicious administrators may capture and leak data. In order to realize privacy preservation, sensitive data should be encrypted before outsourcing. In this paper, we present a secure and practical system over encrypted cloud data, called QSDB (queryable and secure database), which simultaneously supports SQL query operations. The proposed system can store and process the floating point numbers without compromising the security of data. To balance tradeoff between data privacy protection and query processing efficiency, QSDB utilizes three different encryption models to encrypt data. Our strategy is to process as much queries as possible at the cloud server. Encryption of queries and decryption of encrypted queries results are performed at client. Experiments on the real-world data sets were conducted to demonstrate the efficiency and practicality of the proposed system.


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Cite this article

[IEEE Style]
Guoxiu Liu, Geng Yang, Haiwei Wang, Hua Dai and Qiang Zhou, "QSDB: An Encrypted Database Model for Privacy-Preserving in Cloud Computing," KSII Transactions on Internet and Information Systems, vol. 12, no. 7, pp. 3375-3400, 2018. DOI: 10.3837/tiis.2018.07.021

[ACM Style]
Liu, G., Yang, G., Wang, H., Dai, H., and Zhou, Q. 2018. QSDB: An Encrypted Database Model for Privacy-Preserving in Cloud Computing. KSII Transactions on Internet and Information Systems, 12, 7, (2018), 3375-3400. DOI: 10.3837/tiis.2018.07.021