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Scan Statistics on Enron Graphs

Author

Listed:
  • Carey E. Priebe

    (Johns Hopkins University)

  • John M. Conroy

    (IDA Center for Computing Sciences)

  • David J. Marchette

    (NSWC B10)

  • Youngser Park

    (Johns Hopkins University)

Abstract

We introduce a theory of scan statistics on graphs and apply the ideas to the problem of anomaly detection in a time series of Enron email graphs.

Suggested Citation

  • Carey E. Priebe & John M. Conroy & David J. Marchette & Youngser Park, 2005. "Scan Statistics on Enron Graphs," Computational and Mathematical Organization Theory, Springer, vol. 11(3), pages 229-247, October.
    • Handle: RePEc:spr:comaot:v:11:y:2005:i:3:d:10.1007_s10588-005-5378-z
    DOI: 10.1007/s10588-005-5378-z
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    References listed on IDEAS

    as
    1. Chen, Jie & Glaz, Joseph, 1996. "Two-dimensional discrete scan statistics," Statistics & Probability Letters, Elsevier, vol. 31(1), pages 59-68, December.
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    Citations

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    Cited by:

    1. Priebe, Carey E. & Park, Youngser & Marchette, David J. & Conroy, John M. & Grothendieck, John & Gorin, Allen L., 2010. "Statistical inference on attributed random graphs: Fusion of graph features and content: An experiment on time series of Enron graphs," Computational Statistics & Data Analysis, Elsevier, vol. 54(7), pages 1766-1776, July.
    2. Ze Li & Duoyong Sun & Renqi Zhu & Zihan Lin, 2017. "Detecting event-related changes in organizational networks using optimized neural network models," PLOS ONE, Public Library of Science, vol. 12(11), pages 1-21, November.
    3. Jana Diesner & Terrill L. Frantz & Kathleen M. Carley, 2005. "Communication Networks from the Enron Email Corpus “It's Always About the People. Enron is no Different”," Computational and Mathematical Organization Theory, Springer, vol. 11(3), pages 201-228, October.
    4. Anurat Chapanond & Mukkai S. Krishnamoorthy & Bülent Yener, 2005. "Graph Theoretic and Spectral Analysis of Enron Email Data," Computational and Mathematical Organization Theory, Springer, vol. 11(3), pages 265-281, October.
    5. Ramin Moghaddass & Yongtao Guan, 2022. "Optimal Frameworks for Detecting Anomalies in Sensor-Intensive Heterogeneous Networks," INFORMS Journal on Computing, INFORMS, vol. 34(5), pages 2583-2610, September.
    6. N. Lee & C. Priebe, 2011. "A latent process model for time series of attributed random graphs," Statistical Inference for Stochastic Processes, Springer, vol. 14(3), pages 231-253, October.
    7. Joseph Crawford & Tijana Milenković, 2018. "ClueNet: Clustering a temporal network based on topological similarity rather than denseness," PLOS ONE, Public Library of Science, vol. 13(5), pages 1-25, May.
    8. Grothendieck, John & Priebe, Carey E. & Gorin, Allen L., 2010. "Statistical inference on attributed random graphs: Fusion of graph features and content," Computational Statistics & Data Analysis, Elsevier, vol. 54(7), pages 1777-1790, July.

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