source). The information source then infects its neighbors, and the information starts to spread in the network. Now given a snapshot of the network, in which we can identify infected nodes and healthy (susceptible and recovered) nodes (we assume susceptible nodes and recovered nodes are indistinguishable), the question is which node is the information source.

We remark that it is very important to take recovery into consideration since recovery can happen due to various reasons in practice. For example, a contraband material uploader may delete the file, a computer may recover from a virus attack after anti-virus software removes the virus, and a user may delete the rumor from her/his blog. In order to solve the information source detection problem in these scenarios, we study the SIR model in this paper, which makes the problem significantly more challenging than that in the SI model as we will explain in the related work section.

Main Results
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The main results of this paper are summarized below.

-   Similar to the SI model, the information source detection problem can be formalized as an MLE problem. Unfortunately, to solve the MLE problem, we need to consider all possible infection sample paths, and for 