Knowledge representation of network semantics for reasoning-powered cyber-situational awareness
Date
2018
Authors
Sikos, L.F.
Philp, D.
Howard, C.
Voigt, S.
Stumptner, M.
Mayer, W.
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Sikos, L.F.
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Book chapter
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Source details - Title: AI in cybersecurity, 2018 / Sikos, L.F. (ed./s), vol.151, Ch.2, pp.19-45
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Abstract
For network analysts, understanding how network devices are interconnected and how information flows around the network is crucial to the cyber-situational awareness required for applications such as proactive network security monitoring. Many heterogeneous data sources are useful for these applications, including router configuration files, routing messages, and open datasets. However, these datasets have interoperability issues, which can be overcome by using formal knowledge representation techniques for network semantics. Formal knowledge representation also enables automated reasoning over statements about network concepts, properties, entities, and relationships, thereby enabling knowledge discovery. This chapter describes formal knowledge representation formalisms to capture the semantics of communication network concepts, their properties, and the relationships between them, in addition to metadata such as data provenance. It also describes how the expressivity of these knowledge representation mechanisms can be increased to represent uncertainty and vagueness.
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Copyright 2019 Springer Nature