Abstract
Provenance properties help asses the level of trust on the integrity of resources and events. One of the problems of interest is to find the right balance between the expressive power of the provenance specification language and the amount of historical information that needs to be remembered for each resource or event. This gives rise to possibly conflicting objectives relevant to integrity, privacy, and performance. Related problems are how to reduce historical information in a way that the provenance properties of interest are preserved, that is suitable for a distributed setting, and that relies on an incremental construction. We investigate these problems in a simple model of computation where resources/events and their dependencies form an acyclic directed graph, and computation steps consist of addition of new resources and of provenance-based queries. The model is agnostic with respect to the actual provenance specification language. We present then a framework, parametric on such language, for distributing, and incrementally constructing reduced histories in a sound and complete way. In the resulting model of computation, reduced histories are computed incrementally and queries are tested locally on reduced histories. We study different choices for instantiating the framework with concrete provenance specification languages, and their corresponding provenance-preserving history reduction techniques.
This work has been supported by the EU H2020-SU-ICT-03-2018 Project No. 830929 CyberSec4Europe (cybersec4europe.eu).
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Notes
- 1.
Note that we do not introduce self-loop transitions in leaf states/resources. This allows formulae to observe whether a resource has dependencies. Alternatively, loops could have been introduced as usual in CTL semantics. In that case, the ability to observe absence of dependencies can be obtained with a dedicated predicate.
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Lluch Lafuente, A. (2019). A Framework for Provenance-Preserving History Distribution and Incremental Reduction. In: Boreale, M., Corradini, F., Loreti, M., Pugliese, R. (eds) Models, Languages, and Tools for Concurrent and Distributed Programming. Lecture Notes in Computer Science(), vol 11665. Springer, Cham. https://doi.org/10.1007/978-3-030-21485-2_26
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