Channel Abstractions for Network Security

Process algebraic techniques for distributed systems are increasingly being targeted at identifying abstractions adequate both for high-level programming and specification, and for security analysis and verification. Drawing on our earlier work in [Bugliesi & Focardi 2008] F08}, we investigate the expressive power of a core set of security and network abstractions that provide high-level primitives for the specifications of the honest principals in a network, while at the same time enabling an analysis of the network-level adversarial attacks that may be mounted by an intruder. We analyze various bisimulation equivalences for security, arising from endowing the intruder with (i) different adversarial capabilities and (ii) increasingly powerful control on the interaction among the distributed principals of a network. By comparing the relative strength of the bisimulation equivalences, we obtain a direct measure of the discriminating power of the intruder, hence of the expressiveness of the corresponding intruder model

Channel Abstractions for Network Security

Process algebraic techniques for distributed systems are increasingly being targeted at identifying abstractions adequate both for high-level programming and specification, and for security analysis and verification. Drawing on our earlier work in [Bugliesi & Focardi 2008] F08}, we investigate the expressive power of a core set of security and network abstractions that provide high-level primitives for the specifications of the honest principals in a network, while at the same time enabling an analysis of the network-level adversarial attacks that may be mounted by an intruder. We analyze various bisimulation equivalences for security, arising from endowing the intruder with (i) different adversarial capabilities and (ii) increasingly powerful control on the interaction among the distributed principals of a network. By comparing the relative strength of the bisimulation equivalences, we obtain a direct measure of the discriminating power of the intruder, hence of the expressiveness of the corresponding intruder model