A privacy-preserving bucket partition mechanism in cloud

作者：Zhang, Hao; Huang, Tao^*; Liu, Sannv Ya; Wang, Li Na

来源：Chinese Journal of Computers, 2016, 39(2): 429-440.

DOI：10.11897/SP.J.1016.2016.00429

• Ciphertext query
• Database as a services (DaaS)
• Generation algorithm
• Information disclosure
• Information leakage
• Privacy leakages
• Privacy preserving
• Query efficiency

A large number of organizations and institutions have been attracted to the cloud platform for its features, such as convenient management. Thus, the security of the outsourced data become more and more important. Encryption is a useful approach to protecting the data, while the features of the encrypted data are vanished. To manage the data effectively, the efficient and secure ciphertext query approach is urgent. However, the existing ciphertext query technology fails to provide a deep analysis in privacy leakage under attack. To solve this problem, we propose a privacy-preserving bucket partition mechanism in Database as a Service (DAAS) model in cloud. First, this paper proposed a generation algorithm (GA) based bucked partition mechanism according to the query efficiency. Then this paper built a privacy index system for information disclosure during the query and combined the privacy index system with the query efficiency. Finally, this paper optimized the proposed model based on the GA to balance the privacy and the accuracy during the query. The algorithm maximized the query accuracy and efficiency, reduced the information leakage during the query, and consequently enhances the availability and privacy of sensitive data in cloud. To verify the effectiveness of the proposed mechanism, the comparison experiments of our proposed mechanism and other bucket partition mechanisms were done. The result shows that the proposed mechanism is superior to others.

• 出版日期2016
• 单位华中师范大学