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Private Streaming With Convolutional Codes

机译：私人媒体与卷积码

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摘要

Recently, information-theoretic private information retrieval (PIR) from coded storage systems has gained a lot of attention, and a general star product PIR scheme was proposed. In this paper, the star product scheme is adopted, with appropriate modifications, to the case of private (e.g., video) streaming. It is assumed that the files to be streamed are stored on n servers in a coded form, and the streaming is carried out via a convolutional code. The star product scheme is defined for this special case, and various properties are analyzed for two channel models related to straggling and Byzantine servers, both in the baseline case as well as with colluding servers. The achieved PIR rates for the given models are derived and, for the cases where the capacity is known, the first model is shown to be asymptotically optimal, when the number of stripes in a file is large. The second scheme introduced in this work is shown to be the equivalent of block convolutional codes in the PIR setting. For the Byzantine server model, it is shown to outperform the trivial scheme of downloading stripes of the desired file separately without memory.
机译：最近，来自编码存储系统的信息理论私人信息检索（PIR）已经提出了很多关注，并且提出了一般的星级产品PIR方案。在本文中，采用了明星产品方案，以适当的修改，以私有（例如，视频）流的情况。假设要流的文件以编码形式存储在N服务器上，并且通过卷积码来执行流传输。 STAR产品方案是针对该特殊情况定义的，分析了各种属性，用于两个与讨论和拜占庭服务器相关的频道模型，都在基线案例以及拼拼接服务器中。派生了给定模型的实现了PIR率，并且对于该容量所知的情况，当文件中的条纹数量大时，第一模型被显示为渐近最佳。在该工作中引入的第二种方案被示出为PIR设置中的相当于块卷积码。对于拜占庭式服务器模型，显示出优于没有内存的单独下载所需文件条纹的琐碎方案。

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