Abstract
As many domains employ ever more complex systems-of-systems, capturing provenance among component systems is increasingly important. Applications such as intrusion detection, load balancing, traffic routing, and insider threat detection all involve monitoring and analyzing the data provenance. Implicit in these applications is the assumption that “good” provenance is captured (e.g. complete provenance graphs, or one full path). When attempting to provide “good” provenance for a complex system of systems, it is necessary to know “how hard” the provenance-enabling will be and the likely quality of the provenance to be produced. In this work, we provide analytical results and simulation tools to assist in the scoping of the provenance enabling process. We provide use cases of complex systems-of-systems within which users wish to capture provenance. We describe the parameters that must be taken into account when undertaking the provenance-enabling of a system of systems. We provide a tool that models the interactions and types of capture agents involved in a complex systems-of-systems, including the set of known and unknown systems in the environment. The tool provides an estimation of quantity and type of capture agents that will need to be deployed for provenance-enablement in a complex system that is not completely known.
Approved for Public Release #16-0858. The authors’ affiliation with The MITRE Corporation is provided for identification purposes only, and is not intended to convey or imply MITRE’s concurrence with, or support for, the positions, opinions or viewpoints expressed by the author.
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Gammack, D., Scott, S., Chapman, A.P. (2016). Modelling Provenance Collection Points and Their Impact on Provenance Graphs. In: Mattoso, M., Glavic, B. (eds) Provenance and Annotation of Data and Processes. IPAW 2016. Lecture Notes in Computer Science(), vol 9672. Springer, Cham. https://doi.org/10.1007/978-3-319-40593-3_12
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