Decision support for network path estimation via automated reasoning

Abstract

Network path estimation is the problem of finding the best paths between two devices. However, the underpinning communication network information is heterogeneous and derived from disparate sources. Knowledge representation can bridge this gap; however, duplicates, data quality, and reliability issues across the sources raise the need to capture context information. One option is to use RDF quadruples. However, reasoning over such context-aware statements is not trivial; it requires reasoning rules specific to the communication network domain. This paper proposes a method to reason over contextualized statements to improve network path estimation for cybersecurity and cyber-situational awareness.