A particle filter for sequential infection source estimation

Wenchang Tang; Wee Peng Tay

ICASSP 2017accepted0 citations

A particle filter for sequential infection source estimation

Abstract

In this paper we study the problem of identifying an infection source in a network based only on the network topology and a stream of infection timestamps. We propose a sequential source estimation algorithm (SSE) using a particle filter that is based on an approximate hidden Markov chain model, which can be interpreted as a “reverse” propagation process. Simulations using synthetic networks and experiments using real-world social network data suggest that SSE is able to estimate the true infection source to within a small number of hops with less than 20% of the infection timestamps being observed.

BibTeX

@inproceedings{icassp2017_aparticlefilterf,
  title = {A particle filter for sequential infection source estimation},
  author = {Wenchang Tang and Wee Peng Tay},
  booktitle = {ICASSP 2017},
  year = {2017}
}