Optimal and robust epidemic response for multiple networks

We study the optimization of malicious software removal or patch deployment processes across multiple networks. The well-known classical epidemic model is adapted to model malware propagation in this multi-network framework. We capture the trade-off between the infection spread and the patching costs in a cost function, leading to an optimal control problem. We linearize the system to derive feedback controllers using pole-placement, linear quadratic regulator (LQR) optimal control, and H^infin optimal control, where we explicitly model measurement errors in the number of infected clients. The resulting patching strategies are analyzed numerically and their results are compared. The proportional response that is typically assumed for the classical epidemic model is shown to be sub-optimal.