A Characterization of the problem of secure provenance management
2009
- 48Usage
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Usage48
- Abstract Views48
Article Description
Data (or information) provenance has many important applications. However, prior work on data provenance management almost exclusively focused on the collection, representation, query, and storage of provenance data. In contrast, the security aspect of provenance management has not been understood nor adequately addressed. A natural question then is: What would a secure provenance management system - perhaps as an analogy to secure database management systems - look like? In this paper, we explore the problem space of secure provenance management systems with an emphasis on the security requirements for such systems, and characterize desired solutions for tackling the problem. We believe that this paper makes a significant step towards a comprehensive solution to the problem of secure provenance management.
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