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Private information retrieval from MDS coded data in distributed storage systems

机译:从分布式存储系统中的MDS编码数据中检索私人信息

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We consider the problem of providing privacy, in the private information retrieval (PIR) sense, to users requesting data from a distributed storage system (DSS). The DSS uses an (n, k) Maximum Distance Separable (MDS) code to store the data reliably on unreliable storage nodes. Some of these nodes can be spies which report to a third party, such as an oppressive regime, which data is being requested by the user. An information theoretic PIR scheme ensures that a user can satisfy its request while revealing, to the spy nodes, no information on which data is being requested. A user can achieve PIR by downloading all the data in the DSS. However, this is not a feasible solution due to its high communication cost. We construct PIR schemes with low download communication cost. When there is b = 1 spy node in the DSS, we construct PIR schemes with download cost 1/1-R per unit of requested data (R = k is the code rate), achieving the information theoretic limit for linear schemes. The proposed schemes are universal since they depend on the code rate, but not on the generator matrix of the code. When there are 2 ≤ b ≤ n - k spy nodes, we devise linear PIR schemes that have download cost equal to b + k per unit of requested data.
机译:我们考虑了从私有信息检索(PIR)的意义上向向分布式存储系统(DSS)请求数据的用户提供隐私的问题。 DSS使用(n,k)最大距离可分离(MDS)代码将数据可靠地存储在不可靠的存储节点上。这些节点中的一些可以是向第三方报告的间谍,例如压迫性政权,该数据正在由用户请求。信息理论上的PIR方案可确保用户可以满足其请求,同时不向间谍节点显示有关正在请求哪些数据的信息。用户可以通过下载DSS中的所有数据来实现PIR。然而,由于其高通信成本,这不是可行的解决方案。我们构建下载通信成本较低的PIR方案。当DSS中有b = 1个间谍节点时,我们构建PIR方案,每单位请求数据的下载成本为1 / R(R = k / n是编码速率),从而达到了线性方案的信息理论极限。所提出的方案是通用的,因为它们取决于代码率,而不取决于代码的生成器矩阵。当存在2≤b≤n-k个间谍节点时,我们设计了线性PIR方案,其下载成本等于每单位请求数据的b + k。

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