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User Rank: A User Influence-Based Data Distribution Optimization Method for Privacy Protection in Cloud Storage System

机译:用户等级:云存储系统中基于用户影响力的数据分发优化隐私保护方法

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摘要

The spring up of cloud storage, such as Hadoop HDFS, Open Stack Swift, brings us more intelligent storage solutions. Nowadays, the most commercial version of cloud storage system puts more emphasis on high-performance and high-availability, very little attention is given to privacy protection. This paper proposes a user influence-based data distribution optimization method, User Rank, which migrate blocks of high-impact data from threatened nodes to secure nodes. Additionally, a reference implementation of User Rank is presented to optimize cloud storage system. The simulation experiments results verify that User Rank can significantly reduce private leakage for private or public cloud.
机译:Hadoop HDFS,Open Stack Swift等云存储的兴起,为我们带来了更多的智能存储解决方案。如今,最商业化的云存储系统版本更加注重高性能和高可用性,而对隐私保护的关注却很少。本文提出了一种基于用户影响的数据分配优化方法,即用户等级,该方法将高影响力数据块从受威胁的节点迁移到安全的节点。另外,提出了用户等级的参考实现以优化云存储系统。仿真实验结果证明,用户等级可以显着减少私有云或公共云的私有泄漏。

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