Ateniese, Goodrich, Lekakis, Papamanthou, Paraskevas, and Tamassia introduced the Accountable Storage protocol, which is a way for a client to outsource their data to a cloud storage provider while allowing the client to periodically perform accountability challenges. An accountability challenge efficiently recovers any pieces of data the server has lost or corrupted, allowing the client to extract the original copies of the damaged or lost data objects. A severe limitation of the prior accountable storage scheme of Ateniese et al., however, is that it is not fully dynamic. That is, it does not allow a client to freely insert and delete data from the outsourced data set after initializing the protocol, giving the protocol limited practical use in the real world. In this paper, we present Dynamic Accountable Storage, which is an efficient way for a client to periodically audit their cloud storage while also supporting insert and delete operations on the data set. To do so, we introduce a data structure, the IBLT tree, which allows either the server or the client to reconstruct data the server has lost or corrupted in a space-efficient way.

翻译：Ateniese、Goodrich、Lekakis、Papamanthou、Paraskevas和Tamassia提出的可问责存储协议，使客户能够将数据外包至云存储服务商，同时允许客户定期执行可问责性挑战。可问责性挑战能高效恢复服务器丢失或损坏的任何数据片段，使客户能够提取受损或丢失数据对象的原始副本。然而，Ateniese等人先前提出的可问责存储方案存在严重局限：它并非完全动态。这意味着协议初始化后，客户无法自由地在已外包数据集中插入或删除数据，导致该协议在现实世界中的实际应用受限。本文提出动态可问责存储方案，使客户在定期审计云存储的同时，能够对数据集执行插入与删除操作。为此，我们引入一种名为IBLT树的数据结构，该结构允许服务器或客户端以空间高效的方式重构服务器丢失或损坏的数据。