Defense Strategies for Asymmetric Networked Systems with Discrete Components

• Published in: Sensors (Basel, Switzerland) Switzerland), 2018-05, Vol.18 (5), p.1421
• Main Authors: Rao, Nageswara S V, Ma, Chris Y T, Hausken, Kjell, He, Fei, Yau, David K Y, Zhuang, Jun
• Format: Article
• Language: English
• Subjects: aggregated correlation functions; Correlation; cyber-physical infrastructures; Equilibrium conditions; Infrastructure; networked systems; OTHER INSTRUMENTATION; sum-form, product-form and composite utility functions; Survival
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s18051421

We consider infrastructures consisting of a network of systems, each composed of discrete components. The network provides the vital connectivity between the systems and hence plays a critical, asymmetric role in the infrastructure operations. The individual components of the systems can be attacked by cyber and physical means and can be appropriately reinforced to withstand these attacks. We formulate the problem of ensuring the infrastructure performance as a game between an attacker and a provider, who choose the numbers of the components of the systems and network to attack and reinforce, respectively. The costs and benefits of attacks and reinforcements are characterized using the sum-form, product-form and composite utility functions, each composed of a survival probability term and a component cost term. We present a two-level characterization of the correlations within the infrastructure: (i) the aggregate failure correlation function specifies the infrastructure failure probability given the failure of an individual system or network, and (ii) the survival probabilities of the systems and network satisfy first-order differential conditions that capture the component-level correlations using multiplier functions. We derive Nash equilibrium conditions that provide expressions for individual system survival probabilities and also the expected infrastructure capacity specified by the total number of operational components. We apply these results to derive and analyze defense strategies for distributed cloud computing infrastructures using cyber-physical models.