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Attack graphs are models that offer significant cap
abilities to analyse security in network systems. A
n
attack graph allows the representation of vulnerabi
lities, exploits and conditions for each attack in
a single
unifying model. This paper proposes a methodology
to explore the graph using a genetic algorithm (GA)
.
Each attack path is considered as an independent at
tack scenario from the source of attack to the targ
et.
Many such paths form the individuals in the evoluti
onary GA solution. The populationbased strategy of
a
GA provides a natural way of exploring a large numb
er of possible attack paths to find the paths that
are
most important. Thus unlike many other optimisation
solutions a range of solutions can be presented to
a
user of the methodology.
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