Maximum likelihood rumor source detection in a star network

Sam Spencer, R. Srikant

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

Abstract

Here we examine the problem of rumor source identification in star networks. We assume the SI model for rumor propagation with exponential waiting times. We consider the case where a rumor originates from a single source, and find an explicit, non-iterative, maximum likelihood estimate for the source given the observed infection pattern. The theoretical derivation is supported by computational data. We contrast this estimator with the «rumor center» estimator of Shah and Zaman. Unlike rumor centrality, our ML estimator admits the possibility of more than two equiprobable maxima for a given infection pattern, and while a unique rumor center is always equivalent to the distance center, we show that this is not the case for our ML estimator.

Original languageEnglish (US)
Title of host publication2016 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2199-2203
Number of pages5
ISBN (Electronic)9781479999880
DOIs
StatePublished - May 18 2016
Event41st IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 - Shanghai, China
Duration: Mar 20 2016Mar 25 2016

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume2016-May
ISSN (Print)1520-6149

Other

Other41st IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016
CountryChina
CityShanghai
Period3/20/163/25/16

Keywords

  • Infection source identification
  • SI model
  • maximum likelihood
  • rumor source identification
  • star network

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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  • Cite this

    Spencer, S., & Srikant, R. (2016). Maximum likelihood rumor source detection in a star network. In 2016 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 - Proceedings (pp. 2199-2203). [7472067] (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings; Vol. 2016-May). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICASSP.2016.7472067