We study the problem of identifying a single infection source in a network
under the susceptible-infected-recovered-infected (SIRI) model. We describe the
infection model via a state-space model, and utilizing a state propagation
approach, we derive an algorithm known as the heterogeneous infection spreading
source (HISS) estimator, to infer the infection source. The HISS estimator uses
the observations of node states at a particular time, where the elapsed time
from the start of the infection is unknown. It is able to incorporate side
information (if any) of the observed states of a subset of nodes at different
times, and of the prior probability of each infected or recovered node to be
the infection source. Simulation results suggest that the HISS estimator
outperforms the dynamic message pass- ing and Jordan center estimators over a
wide range of infection and reinfection rates.Comment: 5 pages, 3 figures; to present in ICASSP 201