首页> 外文期刊>Knowledge-Based Systems >Privacy preserving service selection using fully homomorphic encryption scheme on untrusted cloud service platform
【24h】

Privacy preserving service selection using fully homomorphic encryption scheme on untrusted cloud service platform

机译:在不受信任的云服务平台上使用完全同态加密方案选择隐私保护服务

获取原文
获取原文并翻译 | 示例
           

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 (FHE) 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. (C) 2019 Elsevier B.V. All rights reserved.
机译:在本文中,我们提出了一种基于云的服务系统的隐私保护服务选择框架。在基于云的服务系统中,云提供商根据其服务质量(QoS)信息从一组服务中选择最佳服务。从服务提供商的角度来看,服务的QoS信息是敏感的。我们声称云中的服务选择过程可能会产生偏差。服务提供商可以贿赂云提供商的不诚实员工,以在服务选择过程中利用不正当优势。因此,执行服务选择任务以使QoS信息保持私有很重要。我们在本文中使用完全同态加密(FHE)方案来加密QoS值。云提供商在加密的QoS值上执行服务选择任务,以确保隐私。为了减少计算开销,我们提出了用于并行执行的MapReduce模型。我们进行了一些实验,以使用合成QoS数据集评估我们提出的隐私保留服务选择框架的性能。 (C)2019 Elsevier B.V.保留所有权利。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号