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Database provenance chronicles the history of updates and modifications to data, and has received much attention due to its central role in scientific data management. However, the use of provenance information still requires a leap of faith. Without additional protections, provenance records are vulnerable to accidental corruption, and even malicious forgery, a problem that is most pronounced in the loosely-coupled multi-user environments often found in scientific research. This paper investigates the problem of providing integrity and tamper-detection for database provenance. The authors propose a checksum-based approach, which is well-suited to the unique characteristics of database provenance, including non-linear provenance objects and provenance associated with multiple fine granularities of data.
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