Assessing network vulnerability under probabilistic region failure model

The mission critical network infrastructures are facing potential large region threats, both intentional (like EMP attack, bomb explosion) and natural (like earthquake, flooding). The available research on region failure related vulnerability studies generally adopt a kind of simple “deterministic” region failure models, which can not capture some important features of real region failure scenarios, where a network component in the region only fails with certain probability, and more importantly, such failure probability tends to vary with both its dimension and its distance to failure center. In this paper, we provide a more general “probabilistic” region failure model to capture the key features of a region failure and apply it for the network vulnerability assessment. To facilitate such assessment, we adopt a grid partition-based scheme to estimate various statistical network metrics under a random region failure. A theoretical framework is also established to determine a suitable grid partition such that a specified estimation error requirement is satisfied. The grid partition technique is also useful for identifying the vulnerable zones of a network, which can guide network designers to initiate proper network protection against such failures. The work in this paper helps us more deeply understand the network vulnerability behavior under region failure and facilitates the design and maintenance of future highly survivable mission critical networks.