  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.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. Concretely, 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.
