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11

ISI
2007
Springer

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Detecting Anomalies in Graphs

13 years 10 months ago

Detecting Anomalies in Graphs

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Graph data represents relationships, connections, or aﬃnities. Innocent relationships produce repeated, and so common, substructures in graph data. We present techniques for discovering anomalous substructures in graphs, for example small cliques, nodes with unusual neighborhoods, or small unusual subgraphs, using extensions of spectral graph techniques commonly used for clustering. Although not all anomalous structure represents terrorist or criminal activity, it is plausible that all terrorist or criminal activity creates anomalous substructure in graph data. Using our techniques, unusual regions of a graph can be selected for deeper analysis.

David B. Skillicorn

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Anomalous Substructure | Data Represents Relationships | Graph Data | ISI 2007 | Security Privacy |

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Added	08 Jun 2010
Updated	08 Jun 2010
Type	Conference
Year	2007
Where	ISI
Authors	David B. Skillicorn

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