Detecting anomalies in cargo using graph properties

Authors:
William Eberle;Lawrence Holder
Affiliations:
Department of Computer Science and Engineering, University of Texas at Arlington, Arlington, TX;Department of Computer Science and Engineering, University of Texas at Arlington, Arlington, TX
Venue:
ISI'06 Proceedings of the 4th IEEE international conference on Intelligence and Security Informatics
Year:
2006

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Abstract

The ability to mine relational data has become important in several domains (e.g., counter-terrorism), and a graph-based representation of this data has proven useful in detecting various relational, structural patterns [1]. Here, we analyze the use of graph properties as a method for uncovering anomalies in data represented as a graph.