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Formal Policy-Based Provenance Audit

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Part of the Lecture Notes in Computer Science book series (LNSC,volume 9836)

Abstract

Data processing within large organisations is often complex, impeding both the traceability of data and the compliance of processing with usage policies. The chronology of the ownership, custody, or location of data—its provenance—provides the necessary information to restore traceability. However, to be of practical use, provenance records should include sufficient expressiveness by design with a posteriori analysis in mind, e.g. the verification of their compliance with usage policies. Additionally, they ought to be combined with systematic reasoning about their correctness. In this paper, we introduce a formal framework for policy-based provenance audit. We show how it can be used to demonstrate correctness, consistency, and compliance of provenance records with machine-readable usage policies. We also analyse the suitability of our framework for the special case of privacy protection. A formalised perspective on provenance is also useful in this area, but it must be integrated into a larger accountability process involving data protection authorities to be effective. The practical applicability of our approach is demonstrated using a provenance record involving medical data and corresponding privacy policies with personal data protection as a goal.

Keywords

  • Privacy Policy
  • Personal Data
  • Policy Language
  • Data Subject
  • Data Controller

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Notes

  1. 1.

    In the scope of accountability as a data protection principle [3], this proof-of-compliance requirement is not limited to high-level statements of intent, but is often seen as incorporating a practical level as well, i.e. concrete data handling actions [9].

  2. 2.

    In practice, data subjects may delegate the power of negotiating policies to a third party they trust.

  3. 3.

    For instance, a linking policy can prevent de-anonymisation.

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Acknowledgments

This work has been co-funded by the DFG as part of project “Long-Term Secure Archiving” within the CRC 1119 CROSSING. In addition, it has received funding from the European Union’s Horizon 2020 research and innovation program under Grant Agreement No 644962. The authors thank Fanny Coudert for insights about purpose ontologies.

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Butin, D., Demirel, D., Buchmann, J. (2016). Formal Policy-Based Provenance Audit. In: Ogawa, K., Yoshioka, K. (eds) Advances in Information and Computer Security. IWSEC 2016. Lecture Notes in Computer Science(), vol 9836. Springer, Cham. https://doi.org/10.1007/978-3-319-44524-3_14

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