Optimal quarantining strategy of suppressing interdependent epidemics spreading over complex networks is a critical issue. In this paper, we first establish a framework to capture the coupling between two epidemics, and then analyze the system's equilibrium states by categorizing them into three classes, and deriving their stability conditions. The designed quarantining strategy globally optimizes the trade-off between the quarantining cost and the severity of epidemics in the network. In addition, we provide structural results on the predictability of epidemic spreading by showing the existence and uniqueness of the solution. We also demonstrate the robustness of quarantining strategy by showing the continuity of epidemic severity with respect to the applied quarantining effort. A gradient descent algorithm based on a fixed-point iterative scheme is proposed to find the optimal quarantining strategy. Depending on the system parameters, the quarantining strategy can lead to switching between equilibria of the interdependent epidemic network as the control cost varies. Finally, we use case studies to corroborate and illustrate the obtained theoretical results.