Privacy-Preserving Storage in the Fog

Michael Fabsich, Dominik Kaaser, Vasileios Karagiannis, Stefan Schulte
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Abstract

In recent years cloud storage services have gained much attention and become a commodity to companies and private users. Nevertheless, cloud storage services have some limitations, especially related to privacy, latency, and availability. In this work we propose a distributed storage system which tackles the major limitations of classical cloud storage services. To this end, we design and implement a storage system which combines classical cloud storage services with the approach of fog computing by using resources at the edge of the network. At the core of our system lies a placement strategy which distributes the data to different storage components. Our implementation is based on well-established methods and techniques from information theory and cryptography. Our empirical analysis shows that our system preserves privacy, provides low latency, and offers high availability. Most notably, we reduce the latency by up to 42% in Upload Mode and even by up to 76% in Download Mode compared to a cloud-only solution.
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雾中的隐私保护存储
近年来,云存储服务受到了广泛关注,成为企业和私人用户的一种商品。然而,云存储服务有一些限制,特别是在隐私、延迟和可用性方面。在这项工作中,我们提出了一个分布式存储系统,解决了传统云存储服务的主要局限性。为此,我们利用网络边缘资源,设计并实现了一个将经典云存储服务与雾计算方法相结合的存储系统。我们系统的核心是放置策略,它将数据分配到不同的存储组件。我们的实现基于信息论和密码学的成熟方法和技术。我们的实证分析表明,我们的系统保护了隐私,提供了低延迟,并提供了高可用性。最值得注意的是,与纯云解决方案相比,我们在上传模式下减少了42%的延迟,甚至在下载模式下减少了76%。
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