Blockchain has emerged as a decentralized and distributed framework that enables tamper-resilience and, thus, practical immutability for stored data. This immutability property is important in scenarios where auditability is desired, such as in maintaining access logs for sensitive healthcare and biomedical data. However, the underlying data structure of blockchain, by default, does not provide capabilities to efficiently query the stored data. In this investigation, we show that it is possible to efficiently run complex audit queries over the access log data stored on blockchains by using additional key-value stores. This paper specifically reports on the approach we designed for the blockchain track of iDASH Privacy & Security Workshop 2018 competition. In this track, participants were asked to devise an efficient way to run conjunctive equality and range queries on a genomic dataset access log trail after storing it in a permissioned blockchain network consisting of 4 identical nodes, each representing a different site, created with the Multichain platform. Multichain duplicates and indexes blockchain data locally at each node in a key-value store to support retrieval requests at a later point in time. To efficiently leverage the key-value storage mechanism, we applied various techniques and optimizations, such as bucketization, simple data duplication and batch loading by accounting for the required query types of the competition and the interface provided by Multichain. Particularly, we implemented our solution and compared its loading and query-response performance with SQLite, a commonly used relational database, using the data provided by the iDASH 2018 organizers. Depending on the query type and the data size, the run time difference between blockchain based query-response and SQLite based query-response ranged from 0.2 seconds to 6 seconds. A deeper inspection revealed that range queries were the bottleneck of our solution which, nevertheless, scales up linearly. This investigation demonstrates that blockchain-based systems can provide reasonable query-response times to complex queries even if they only use simple key-value stores to manage their data. Consequently, we show that blockchains may be useful for maintaining data with auditability and immutability requirements across multiple sites.

中文翻译：

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利用区块链在多个站点之间进行不变的日志记录和查询。

区块链已经成为一种分散的，分布式的框架，可以实现篡改复原力，从而实现存储数据的实际不变性。在需要可审核性的情况下，例如维护敏感医疗保健和生物医学数据的访问日志时，这种不变性属性非常重要。但是，默认情况下，区块链的基础数据结构不提供有效查询已存储数据的功能。在这项调查中，我们表明可以通过使用其他键值存储对存储在区块链上的访问日志数据有效地运行复杂的审计查询。本文专门报道了我们为iDASH Privacy and Security Workshop 2018竞赛的区块链追踪设计的方法。在这首单曲中 参与者被要求设计一种有效的方法，将其存储在由4个相同的节点组成的许可的区块链网络中，对基因组数据集访问日志轨迹进行联合相等性和范围查询，该网络由4个相同的节点组成，每个节点代表一个不同的站点，由Multichain平台创建。多链在键值存储中的每个节点本地复制和索引区块链数据，以支持稍后的检索请求。为了有效利用键值存储机制，我们通过考虑竞争所需的查询类型和Multichain提供的接口，应用了各种技术和优化，例如存储桶化，简单的数据复制和批量加载。特别是，我们实施了我们的解决方案，并将其加载和查询响应性能与SQLite进行了比较，使用iDASH 2018组织者提供的数据的常用关系数据库。根据查询类型和数据大小，基于区块链的查询响应和基于SQLite的查询响应之间的运行时差为0.2秒至6秒。更深入的检查表明，范围查询是我们解决方案的瓶颈，但是，它仍会线性扩展。这项调查表明，基于区块链的系统即使仅使用简单的键值存储来管理数据，也可以为复杂的查询提供合理的查询响应时间。因此，我们证明了区块链对于维护跨多个站点具有可审计性和不变性要求的数据可能有用。基于区块链的查询响应与基于SQLite的查询响应之间的运行时差介于0.2秒到6秒之间。更深入的检查表明，范围查询是我们解决方案的瓶颈，但是，它仍会线性扩展。这项调查表明，基于区块链的系统即使仅使用简单的键值存储来管理数据，也可以为复杂的查询提供合理的查询响应时间。因此，我们证明了区块链对于维护跨多个站点具有可审核性和不变性要求的数据可能有用。基于区块链的查询响应与基于SQLite的查询响应之间的运行时差介于0.2秒到6秒之间。更深入的检查表明，范围查询是我们解决方案的瓶颈，但是，解决方案仍会线性扩展。这项调查表明，基于区块链的系统即使仅使用简单的键值存储来管理数据，也可以为复杂的查询提供合理的查询响应时间。因此，我们证明了区块链对于维护具有跨多个站点的可审核性和不变性要求的数据可能有用。这项调查表明，基于区块链的系统即使仅使用简单的键值存储来管理数据，也可以为复杂的查询提供合理的查询响应时间。因此，我们证明了区块链对于维护跨多个站点具有可审核性和不变性要求的数据可能有用。这项调查表明，基于区块链的系统即使仅使用简单的键值存储来管理数据，也可以为复杂的查询提供合理的查询响应时间。因此，我们证明了区块链对于维护具有跨多个站点的可审核性和不变性要求的数据可能有用。