Semantics-based threat structure mining

N. Adam, V. Atluri, V. P. Janeja, A. Paliwal, M. Youssef, S. Chun, J. Cooper, J. Paczkowski, C. Bornhoevd, I. Nassi, J. Schaper

Research output: Contribution to conferencePaperpeer-review


Today's National and Interstate border control agencies are flooded with alerts generated from various monitoring devices. There is an urgent need to uncover potential threats to effectively respond to an event. In this paper, we propose a Semantic Threat Mining approach, to discover threats using the spatio-temporal and semantic relationships among events and data. We represent the potentially dangerous collusion relationships with a Semantic Graph. Using domain-specific ontology of known dangerous relationships, we construct an Enhanced Semantic Graph (ESG) by scoring the edges of the semantic graph and prune it. We further analyze ESG using centrality, cliques and isomorphism to mine the threat patterns. We present a Semantic Threat Mining prototype system in the domain of known dangerous combination of chemicals used in explosives.

Original languageEnglish (US)
Number of pages2
StatePublished - 2006
Event7th Annual International Conference on Digital Government Research, Dg.o 2006 - San Diego, CA, United States
Duration: May 21 2006May 24 2006


Other7th Annual International Conference on Digital Government Research, Dg.o 2006
Country/TerritoryUnited States
CitySan Diego, CA

All Science Journal Classification (ASJC) codes

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications


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