Conventional game-theoretic models of systemic risk evaluation and mitigation in networks with selfish components are based on classical economics which assumes risk neutral/averse decision makers. While the corresponding game-theoretic models have unique Nash equilibrium, our analysis of the Susceptible-Infected-Susceptible (SIS) contagion under behavioral economic model for selfish components, indicates a possibility of multiple Nash equilibria. This possibility has important practical implications, e.g., “unacceptably” high Price of Anarchy (PoA) associated with “non-efficient” Nash equilibria may warrant additional mechanism for the purpose of avoidance of inefficient Nash equilibria. Infeasibility of centralized control of dynamic processes in large-scale networks motivates interest in decentralized strategies. However, decentralized mitigation of the systemic risk, which is inherently a collective phenomenon, requires some level of global view by individual network components. On an example of SIS contagion, we suggest that this global view can be provided with few system-wide “macro-parameters.” Finally, we report our initial results on microeconomic modeling of cyber security investments.