Int. J. of Big Data Intelligence   »   2016 Vol.3, No.3

 

 

Title: PQsel: combining privacy with quality of service in cloud service selection

 

Authors: Li Lin; Tingting Liu; Jian Hu; Jian Ni

 

Addresses:
College of Computer Science, Beijing University of Technology, No. 100, Pingleyuan, Chaoyang District, Beijing, China; National Engineering Laboratory for Classified Information Security Protection, No. 100, Pingleyuan, Chaoyang District, Beijing, China
College of Computer Science, Beijing University of Technology, No. 100, Pingleyuan, Chaoyang District, Beijing, China
College of Computer Science, Beijing University of Technology, No. 100, Pingleyuan, Chaoyang District, Beijing, China
College of Computer Science, Beijing University of Technology, No. 100, Pingleyuan, Chaoyang District, Beijing, China

 

Abstract: Big data analytics and management often need to exploit the processing and storage power of cloud computing. It is obviously important to choose a cloud service with good quality. Meanwhile, users fear data leakage and loss of privacy if their sensitive data is processed in the cloud. In this paper, we propose a novel cloud service selection method, called PQsel, where a cloud service is estimated by colligating its capability of privacy protection (CoPP) and quality of service (QoS). Using a fuzzy comprehensive evaluation technique and AHP-based approach, we calculate the CoPP of each cloud service based on the CoPPs of security mechanisms covering the entire data life-cycle. Furthermore, QoS-driven approaches are introduced to support the privacy-aware cloud selection. An example analysis is given to prove the reasonableness of the proposed method. Comprehensive experiments have been conducted, which demonstrate the effectiveness of the proposed method.

 

Keywords: cloud services; service selection; privacy protection; privacy preservation; data life cycle; quality of service; QoS; analytical hierarchy process; AHP; fuzzy comprehensive evaluation; fuzzy logic.

 

DOI: 10.1504/IJBDI.2016.078411

 

Int. J. of Big Data Intelligence, 2016 Vol.3, No.3, pp.202 - 214

 

Submission date: 31 Mar 2015
Date of acceptance: 20 Oct 2015
Available online: 10 Aug 2016

 

 

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