Matched filtering for subgraph detection in dynamic networks

Benjamin A. Miller, Michelle S. Beard, Nadya Bliss

Research output: Chapter in Book/Report/Conference proceedingConference contribution

19 Citations (Scopus)

Abstract

Graphs are high-dimensional, non-Euclidean data, whose utility spans a wide variety of disciplines. While their non-Euclidean nature complicates the application of traditional signal processing paradigms, it is desirable to seek an analogous detection framework. In this paper we present a matched filtering method for graph sequences, extending to a dynamic setting a previous method for the detection of anomalously dense subgraphs in a large background. In simulation, we show that this temporal integration technique enables the detection of weak subgraph anomalies than are not detectable in the static case. We also demonstrate background/foreground separation using a real background graph based on a computer network.

Original languageEnglish (US)
Title of host publicationIEEE Workshop on Statistical Signal Processing Proceedings
Pages509-512
Number of pages4
DOIs
StatePublished - 2011
Externally publishedYes
Event2011 IEEE Statistical Signal Processing Workshop, SSP 2011 - Nice, France
Duration: Jun 28 2011Jun 30 2011

Other

Other2011 IEEE Statistical Signal Processing Workshop, SSP 2011
CountryFrance
CityNice
Period6/28/116/30/11

Fingerprint

Dynamic Networks
Computer networks
Subgraph
Signal processing
Filtering
Graph in graph theory
Computer Networks
Anomaly
Signal Processing
High-dimensional
Paradigm
Demonstrate
Background
Simulation

Keywords

  • community detection
  • dynamic graphs
  • graph algorithms
  • matched filtering
  • signal detection theory

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Applied Mathematics
  • Signal Processing
  • Computer Science Applications

Cite this

Miller, B. A., Beard, M. S., & Bliss, N. (2011). Matched filtering for subgraph detection in dynamic networks. In IEEE Workshop on Statistical Signal Processing Proceedings (pp. 509-512). [5967745] https://doi.org/10.1109/SSP.2011.5967745

Matched filtering for subgraph detection in dynamic networks. / Miller, Benjamin A.; Beard, Michelle S.; Bliss, Nadya.

IEEE Workshop on Statistical Signal Processing Proceedings. 2011. p. 509-512 5967745.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Miller, BA, Beard, MS & Bliss, N 2011, Matched filtering for subgraph detection in dynamic networks. in IEEE Workshop on Statistical Signal Processing Proceedings., 5967745, pp. 509-512, 2011 IEEE Statistical Signal Processing Workshop, SSP 2011, Nice, France, 6/28/11. https://doi.org/10.1109/SSP.2011.5967745
Miller BA, Beard MS, Bliss N. Matched filtering for subgraph detection in dynamic networks. In IEEE Workshop on Statistical Signal Processing Proceedings. 2011. p. 509-512. 5967745 https://doi.org/10.1109/SSP.2011.5967745
Miller, Benjamin A. ; Beard, Michelle S. ; Bliss, Nadya. / Matched filtering for subgraph detection in dynamic networks. IEEE Workshop on Statistical Signal Processing Proceedings. 2011. pp. 509-512
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