Confidence Sets for the Source of a Diffusion in Regular Trees

We study the problem of identifying the source of a diffusion spreading over a regular tree. When the degree of each node is at least three, we show that it is possible to construct confidence sets for the diffusion source with size independent of the number of infected nodes. Our estimators are motivated by analogous results in the literature concerning identification of the root node in preferential attachment and uniform attachment trees. At the core of our proofs is a probabilistic analysis of Pólya urns corresponding to the number of uninfected neighbors in specific subtrees of the infection tree. We also provide an example illustrating the shortcomings of source estimation techniques in settings where the underlying graph is asymmetric.

[1]  C. Jordan Sur les assemblages de lignes. , 1869 .

[2]  Roy M. Anderson,et al.  The Population Dynamics of Infectious Diseases: Theory and Applications , 1982, Population and Community Biology.

[3]  Michael Fuchs,et al.  Rumor source detection for rumor spreading on random increasing trees , 2015 .

[4]  Devavrat Shah,et al.  Rumors in a Network: Who's the Culprit? , 2009, IEEE Transactions on Information Theory.

[5]  Lei Ying,et al.  Source Localization in Networks: Trees and Beyond , 2015, ArXiv.

[6]  Sanjeev Khanna,et al.  The Power of Local Information in Social Networks , 2012, WINE.

[7]  A. Rapoport Spread of information through a population with socio-structural bias: I. Assumption of transitivity , 1953 .

[8]  Michael Kearns,et al.  Local Algorithms for Finding Interesting Individuals in Large Networks , 2010, ICS.

[9]  Martin Vetterli,et al.  Locating the Source of Diffusion in Large-Scale Networks , 2012, Physical review letters.

[10]  N. Ling The Mathematical Theory of Infectious Diseases and its applications , 1978 .

[11]  Lei Ying,et al.  Information source detection in the SIR model: A sample path based approach , 2012, 2013 Information Theory and Applications Workshop (ITA).

[12]  Luc Devroye,et al.  Finding Adam in random growing trees , 2014, Random Struct. Algorithms.

[13]  W. Sudderth,et al.  Polya Trees and Random Distributions , 1992 .

[14]  Alexander Grey,et al.  The Mathematical Theory of Infectious Diseases and Its Applications , 1977 .

[15]  Alan M. Frieze,et al.  Looking for vertex number one , 2014, ArXiv.

[16]  M. Newman Spread of epidemic disease on networks. , 2002, Physical review. E, Statistical, nonlinear, and soft matter physics.

[17]  Albert,et al.  Emergence of scaling in random networks , 1999, Science.

[18]  Fred B. Schneider,et al.  A Theory of Graphs , 1993 .

[19]  Alessandro Vespignani,et al.  Epidemic spreading in scale-free networks. , 2000, Physical review letters.

[20]  Massimo Franceschetti,et al.  Rumor source detection under probabilistic sampling , 2013, 2013 IEEE International Symposium on Information Theory.

[21]  W. O. Kermack,et al.  A contribution to the mathematical theory of epidemics , 1927 .

[22]  Nellie Clarke Brown Trees , 1896, Savage Dreams.

[23]  Martina Morris,et al.  Epidemiology and Social Networks: , 1993 .

[24]  Devavrat Shah,et al.  Rumor centrality: a universal source detector , 2012, SIGMETRICS '12.

[25]  S. Strogatz Exploring complex networks , 2001, Nature.