Practical applications of performance modelling of security protocols using PEPA

PhD ThesisTrade-off between security and performance has become an intriguing area in recent years in both the security and performance communities. As the security aspects of security protocol research is fully- edged, this thesis is therefore devoted to conducting a performance study of these protocols. The long term objective is to translate formal de nitions of security protocols to formal performance models automatically, then analysing by relevant techniques. In this thesis, we take a preliminary step by studying five typical security protocols, and exploring the methodology of construction and analysis of their models by using the Markovian process algebra PEPA. Through these case studies, an initial framework of performance analysis of security protocol is established. Firstly, a key distribution centre is investigated. The basic model su ers from the commonly encountered state space explosion problem, and so we apply some efficient solution techniques, which include model reduction techniques and ordinary di fferential equation based fluid flow analysis. Finally, we evaluate a utility function for this secure key exchange model. Then, we explore two non-repudiation protocols. Mean value analysis has been applied here for a class of PEPA models, and it is compared with an ODE approximation. After that, an optimistic nonrepudiation protocol with off-line third trust party is studied. The PEPA model has been formulated using a concept of multi-threaded servers with functional rates. The nal case study is a cross-realm Kerberos protocol. A simplified technique of aggregation with an ODE approximation is performed to do efficient cient analysis. All these modelling and analysis methods are illustrated through numerical examples

Studying the effects of adding spatiality to a process algebra model

We use NetLogo to create simulations of two models of disease transmission originally expressed in WSCCS. This allows us to introduce spatiality into the models and explore the consequences of having different contact structures among the agents. In previous work, mean field equations were derived from the WSCCS models, giving a description of the aggregate behaviour of the overall population of agents. These results turned out to differ from results obtained by another team using cellular automata models, which differ from process algebra by being inherently spatial. By using NetLogo we are able to explore whether spatiality, and resulting differences in the contact structures in the two kinds of models, are the reason for this different results. Our tentative conclusions, based at this point on informal observations of simulation results, are that space does indeed make a big difference. If space is ignored and individuals are allowed to mix randomly, then the simulations yield results that closely match the mean field equations, and consequently also match the associated global transmission terms (explained below). At the opposite extreme, if individuals can only contact their immediate neighbours, the simulation results are very different from the mean field equations (and also do not match the global transmission terms). These results are not surprising, and are consistent with other cellular automata-based approaches. We found that it was easy and convenient to implement and simulate the WSCCS models within NetLogo, and we recommend this approach to anyone wishing to explore the effects of introducing spatiality into a process algebra model