A model-based approach for outlier detection in sensor networks

Min Ding*, Qilian Liang, Xiuzhen Cheng, Mznah Al-Rodhaan, Abdullah Al-Dhelaan, Scott C.H. Huang, Dechang Chen

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


In this paper, we propose a model-based approach to detect outliers insensor networks by exploring the spatial correlation among neighboringnodes. This research is motivated by the observation that sensors in closeproximity normally present similar readings.We propose to employ Gaussianmixture modeling as a statistical means to build a probability densityfunction for multivariate spatial neighborhood sensor readings. Outlyingsensors can be reliably detected since they exhibit extremely low densityvalues. Our extensive simulation evaluation validates the proposedmodel-based approach for outlier detection in sensor networks.

Original languageEnglish
Pages (from-to)275-293
Number of pages19
JournalAd-Hoc and Sensor Wireless Networks
Issue number3-4
StatePublished - 2011
Externally publishedYes


  • Expectation-maximimation;wireless sensor networks
  • Gaussian mixture model
  • Outlier detection


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