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The Full Provenance Stack: Five Layers for Complete and Meaningful Provenance

  • 2017
  • OriginalPaper
  • Chapter
Published in:
Authors
Ryan K. L. Ko
Thye Way Phua
Published in
Security, Privacy, and Anonymity in Computation, Communication, and Storage
Publisher
Springer International Publishing

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Abstract

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.

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previous chapter A Novel Bivariate Entropy-Based Network Anomaly Detection System
next chapter Neural Network Based Web Log Analysis for Web Intrusion Detection
Title
The Full Provenance Stack: Five Layers for Complete and Meaningful Provenance
Authors
Ryan K. L. Ko
Thye Way Phua
Copyright Year
2017
Book
Security, Privacy, and Anonymity in Computation, Communication, and Storage

Print ISBN: 978-3-319-72394-5

Electronic ISBN: 978-3-319-72395-2

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-3-319-72395-2_18
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