PIEs: Public Incompressible Encodings for Decentralized Storage

PIEs: Public Incompressible Encodings for Decentralized Storage
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DOI:
10.1145/3319535.3354231
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发表时间:
2019-11
期刊:
Proceedings of the 2019 ACM SIGSAC Conference on Computer and Communications Security
影响因子:
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通讯作者:
Ethan Cecchetti;Ian Miers;A. Juels
Ethan Cecchetti;Ian Miers;A. Juels
中科院分区:
其他
文献类型:
--
作者:
Ethan Cecchetti;Ian Miers;A. Juels

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我们在分布式存储网络(DSN)中提出了一个新的原始支持文件复制,称为公共不可压缩的编码(PIE)。派在具有挑战性的公共DSN设置中运行,其中必须用公共随机性编码和解码文件,而无需加密和保留冗余数据必须是公开验证的。它们可以防止无法检测到的数据压缩,从而使DSN能够使用货币奖励或惩罚来激励经济上理性的服务器正确复制数据。它们的定义还排除了关键,证明了通过ASIC和其他自定义硬件涉及并行性的攻击。我们的PIE结构是第一个通过一个度量获得实验验证的近距离性能的实验验证的近距离性能。与其他可比较的构造不同,它还允许比编码更快地解码数量级。我们使用称为Dagwood Sandwich Graph(DSAG)的图形结构来实现这种高度的安全性和性能,该图是由新颖的深度型图和超级探调器的新颖交流而构建的。派对的性能使它们吸引了DSN,例如拟议的Filecoin系统和以太坊数据碎片。相反,它们的近距离涉及涉及允许任意数据的DSN的实际财务和能源成本的界限。
We present a new primitive supporting file replication in distributed storage networks (DSNs) called a Public Incompressible Encoding (PIE). PIEs operate in the challenging public DSN setting where files must be encoded and decoded with public randomness-i.e., without encryption-and retention of redundant data must be publicly verifiable. They prevent undetectable data compression, allowing DSNs to use monetary rewards or penalties in incentivizing economically rational servers to properly replicate data. Their definition also precludes critical, demonstrated attacks involving parallelism via ASICs and other custom hardware. Our PIE construction is the first to achieve experimentally validated near-optimal performance-within a factor of 4 of optimal by one metric. It also allows decoding orders of magnitude faster than encoding, unlike other comparable constructions. We achieve this high security and performance using a graph construction called a Dagwood Sandwich Graph (DSaG), built from a novel interleaving of depth-robust graphs and superconcentrators. PIEs' performance makes them appealing for DSNs, such as the proposed Filecoin system and Ethereum data sharding. Conversely, their near-optimality establishes concerning bounds on the practical financial and energy costs of DSNs allowing arbitrary data.