In this paper, by applying the game theoretical framework, we propose a new vulnerability identification method in the multicommodity stochastic network. A new performance indicator-expected achievable capacity (EAC)-is proposed to quantify the vulnerability level of network links when the network is attacked by an intelligent adversary. To compute for EAC, a maximin problem is formulated and solved by the method of successive average and linear programming. Reported numerical results on a grid network topology with multiple OD demands show that the effect of network vulnerability can be well represented by the proposed EAC and hence this suggests the usefulness of the proposed network vulnerability analysis framework.

- Game theory
- Queueing theory
- Linear programming
- Extended Access Control
- Network topology
- Grid network
- Utility
- Numerical analysis
- Minimax
- Programming, Linear
- Adversary (cryptography)
- Quantitation
- Game theory
- Queueing theory
- Linear programming
- Extended Access Control
- Network topology
- Grid network
- Utility
- Numerical analysis
- Minimax
- Programming, Linear
- Adversary (cryptography)
- Quantitation