Privacy preserving service selection using fully homomorphic encryption scheme on untrusted cloud service platform
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摘要
In this paper, we present a privacy-preserving service selection framework for cloud-based service systems. In the cloud-based service system, a cloud provider selects the best service from a set of services based on their Quality-of-Service (QoS) information. The QoS information of services is sensitive from the service provider’s point of view. We claim that the service selection process in the cloud can be biased. A service provider can bribe a dishonest employee of the cloud provider for taking unfair advantage during a service selection process. Therefore, it is important to execute the service selection tasks keeping QoS information private. We use a fully homomorphic encryption () scheme in this paper for encrypting QoS values. Service selection task is performed by the cloud provider on encrypted QoS values to ensure privacy. In order to reduce computation overhead, we propose a MapReduce model for parallel execution. We conduct several experiments to evaluate the performance of our proposed privacy preserving service selection framework using synthetic QoS dataset.
论文关键词:Service privacy,Fully homomorphic encryption,Service selection,Untrusted cloud,Cloud services,MapReduce
论文评审过程:Received 13 September 2018, Revised 13 May 2019, Accepted 15 May 2019, Available online 24 May 2019, Version of Record 12 June 2019.
论文官网地址:https://doi.org/10.1016/j.knosys.2019.05.022