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Abstract / Description of output
Using pervasive provenance to secure mainstream systems has recently attracted interest from industry and government. Recording, storing and managing all of the provenance associated with a system is a considerable challenge. Analyzing the resulting noisy, heterogeneous, continuously-growing provenance graph adds to this challenge, and apparently necessitates segmentation, that is, approximating, compressing or summarizing part or all of the graph in order to identify patterns or features. In this paper, we describe this new problem space for provenance data management, contrast it with related problem spaces addressed by prior work on provenance abstraction and sanitization, and highlight challenges and future directions toward solutions to the provenance segmentation problem.
Original language | English |
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Title of host publication | 8th USENIX Workshop on the Theory and Practice of Provenance (TaPP '16) |
Place of Publication | Washington D.C, USA |
Number of pages | 6 |
Publication status | Published - 9 Jun 2016 |
Event | 8th USENIX Workshop on the Theory and Practice of Provenance - Washington D.C, United States Duration: 8 Jun 2016 → 9 Jun 2016 https://www.usenix.org/conference/tapp16 |
Conference
Conference | 8th USENIX Workshop on the Theory and Practice of Provenance |
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Abbreviated title | TaPP 2016 |
Country/Territory | United States |
City | Washington D.C |
Period | 8/06/16 → 9/06/16 |
Internet address |
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