This paper distils three decades of provenance research, and we propose a layered framework, the Full Provenance Stack, for describing provenance completely and meaningfully – within and across machines. The provenance layers aim to proliferate layer protocols and approaches for appropriate data provenance levels of detail, and empower cross-platform features – enabling identifying, detecting, responding and recovering capabilities across all cyber security, digital forensics, and data privacy scenarios.
CITATION STYLE
Ko, R. K. L., & Phua, T. W. (2017). The full provenance stack: Five layers for complete and meaningful provenance. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10658 LNCS, pp. 180–193). Springer Verlag. https://doi.org/10.1007/978-3-319-72395-2_18
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