Estimating the Rumor Source by Rumor Centrality Based Query in Networks


KIPS Transactions on Software and Data Engineering, Vol. 8, No. 7, pp. 275-288, Jul. 2019
https://doi.org/10.3745/KTSDE.2019.8.7.275, Full Text:
Keywords: Rumor Source Detection, Epidemic Models, Maximum Likelihood Estimator, Query
Abstract

In this paper, we consider a rumor source inference problem when sufficiently many nodes heard the rumor in the network. This is an important problem because information spread in networks is fast in many real-world phenomena such as diffusion of a new technology, computer virus/spam infection in the internet, and tweeting and retweeting of popular topics and some of this information is harmful to other nodes. This problem has been much studied, where it has been shown that the detection probability cannot be beyond 31% even for regular trees if the number of infected nodes is sufficiently large. Motivated by this, we study the impact of query that is asking some additional question to the candidate nodes of the source and propose budget assignment algorithms of a query when the network administrator has a finite budget. We perform various simulations for the proposed method and obtain the detection probability that outperforms to the existing prior works.


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Cite this article
[IEEE Style]
J. Choi, "Estimating the Rumor Source by Rumor Centrality Based Query in Networks," KIPS Transactions on Software and Data Engineering, vol. 8, no. 7, pp. 275-288, 2019. DOI: https://doi.org/10.3745/KTSDE.2019.8.7.275.

[ACM Style]
Jaeyoung Choi. 2019. Estimating the Rumor Source by Rumor Centrality Based Query in Networks. KIPS Transactions on Software and Data Engineering, 8, 7, (2019), 275-288. DOI: https://doi.org/10.3745/KTSDE.2019.8.7.275.