In this paper, two models for virus propagation on the Facebook network were proposed.
In the model based on the Facebook application platform, if a virus is installed by more users, it will become more popular and cause more installations.
The result of our simulations showed that, even if the malicious application attracts only a few users in the beginning, it can still spread rapidly. That is because users may trust their friends on Facebook and install the malicious application.
While in the second model, which is similar to email virus propagation, the probability that a user is infected becomes smaller as more and more users get infected.
We found that the virus spreads faster on Facebook than in the original email network, as people use Facebook for entertainment and spend more time on it.
And the network generation models and their parameters can affect the behaviors of virus.
The simulation results of our two virus propagation models showed that, a virus would spread
faster in a network with a greater clustering coefficient, power-law exponent or average degree.