Designing Rating Systems to Promote Mutual Security for Interconnected Networks

—Interconnected autonomous systems (ASs) often share security risks. However, an AS lacks the incentive to make (sufficient) security investments if the cost exceeds its own benefit even though doing that would be socially beneficial. In this paper, we develop a systematic and rigorous framework for analyzing and significantly improving the mutual security of a collection of ASs that interact frequently over a long period of time. Using this framework, we show that simple incentive schemes based on rating systems can be designed to encourage the ASs' security investments, thereby significantly improving their mutual security. When designing the optimal rating systems, we explicitly consider that monitoring the ASs' investment actions is imperfect and that the cyber-environment exhibits unique characteristics. An important consideration in this design is the heterogeneity of ASs in terms of both generated traffic and underlying connectivity. Our analysis shows that the optimal strategy recommended to the ASs on whether to make or not security investments emerges as a tradeoff between the performance gains achieved by ensuring the AS's compliance with the recommended strategy and the efficiency loss induced by the imperfect monitoring. When the monitoring errors are sufficiently small or the traffic and connectivity structure of the AS collection exhibits the " Maximal Critical Traffic (MCT) " property (i.e. the critical traffic of the whole collection is no less than that of any subset of the AS collection), it is optimal to recommend all ASs to make security investments. However, when this network property is not satisfied, an improved performance can be achieved when some ASs are recommended to NOT make security investments. Many simple network topologies (e.g. the complete, the " line " , the " star " graphs and etc.) exhibit the " MCT " property. However, a common topology on the Internet-the " core-periphery " topology-does not possess the " MCT " property and in this case, we prove that whether or not it is optimal to recommend all ASs to make security investments depends on the AS collection size. Even though this paper considers a simplified model of the interconnected ASs' security, our analysis provides important and useful insights for designing rating systems that can significantly improve the mutual security of real networks in a variety of practical scenarios.