A Novel Fast Dimension-Reducing Ranked Query Method with High Security for Encrypted Cloud Data LIU Lianggui and LIU Zhengjin (School of Information Science and Technology, Zhejiang Sci-Tech University, Hangzhou 310018, China)

• Published in: Chinese Journal of Electronics Vol. 29; no. 2; pp. 344 - 350
• Main Authors: Liu, Lianggui, Liu, Zhengjin
• Format: Journal Article
• Language: English
• Published: Published by the IET on behalf of the CIE 01.03.2020
• Subjects: cloud computing; cloud data encryption; cryptography; data dimension reduction; data reduction; data security; Dimension reduction matrix; Encryption search; FDRQM; novel fast dimension‐reducing ranked query method; PCA; principal component analysis; query processing; Security search; data dimension reduction; Security search; cloud data encryption; data security; cryptography; FDRQM; novel fast dimension-reducing ranked query method; PCA; Encryption search; query processing; data reduction; Dimension reduction matrix; cloud computing; principal component analysis
• ISSN: 1022-4653; 2075-5597
• DOI: 10.1049/cje.2020.01.013

We propose a novel Fast dimensionreducing ranked query method (FDRQM) with high security for encrypted cloud data.We use Principal component analysis (PCA) algorithm to improve the speed of data encryption and search efficiency. Moreover, a random threshold of accumulated contribution rate of principal components is set to realize the randomness of data dimension reduction and improve data security further. Besides, we introduce a unit matrix before dimension reduction of index, which can not only improve the security of the system, but also ensure the accuracy of query. We demonstrate that our algorithm is more effective and efficient than existing algorithms.