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Re: coding and nnet's
Bruce Schneier comments:
Neural nets aren't terribly useful for cryptanalysis,
primarily because of the shape of the solution space.
Neural nets work best with problems that have a continuity
of solutions, some better than others. This allows a neural
net to learn, proposing better and better solutions as it
does. Breaking an algorithm provides for very little in the
way of learning opportunities: You either recover the key
or you don't. (At least this is true if the algorithm is
any good.) Neural nets work well in structured environments
where there is something to learn, but not in the
high-entropy, seemingly random world of cryptography.
"Applied Cryptography," second edition, 1996, p. 155.