PQsel: combining privacy with quality of service in cloud service selection
by Li Lin; Tingting Liu; Jian Hu; Jian Ni
International Journal of Big Data Intelligence (IJBDI), Vol. 3, No. 3, 2016

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.

Online publication date: Tue, 16-Aug-2016

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