A privacy-aware cloud service selection method toward data life-cycle

Recent years have witnessed the rapid development of cloud computing, which leverages its unique services to cloud customers in a pay-as-you-go, anytime, anywhere manner. However, a significant barrier to the adoption of cloud services is that users fear data leakage and loss of privacy if their sensitive data is processed in the cloud. Hence, the cloud customer must be able to select appropriate services according to his or her privacy and security needs. In this paper, we propose a novel cloud service selection method called PCSS, where a cloud service is estimated based on its capability of privacy protection (CoPP) covering the entire life-cycle of users´ data. A scalable assessment index system with a 2-level hierarchy structure is constructed to analyze and quantify the CoPP of cloud service. The first-level index is composed of all stages of data life-cycle and the second-level index involves privacy-aware security mechanisms at each stage. We employ a fuzzy comprehensive evaluation technique to count the privacy-preserving value of security mechanism. An AHP- based approach is exploited to decide the impact weight of different security mechanisms to the CoPP of each stage. By calculating a comprehensive CoPP metric of all life-cycle stages, all cloud services can be sorted and recommended to users. An example analysis is given, and the reasonableness of the proposed method is proved. Comprehensive experiments have been conducted, which demonstrate the effectiveness of the proposed method by the comparison with the baseline method at the service selection performance.