Adam Shostack <adam@homeport.org> [...]
Weak systems are thus useful for research and training purposes. I suspect Tim is on the money with a genetic algorithim having a flat `fitness landscape,' but there may be something that a human misses which an evolved algorithim finds.
Also, it may be possible to evolve something against a reduced round version of a cipher (using a training space that is not flat) that will still work better than brute force against a full system. If you have cycles to spare, it might be an interesting avenue of research.
While a well-designed algorithm has a flat search space in the case of a single instance of a particular ciphertext/plaintext, this is not necessarily the case for repeated encryptions using the same key and possibly for other examples (hence differential cryptanalysis, etc.) If there is a way to break a system that is less than a brute-force search of all possible keys then the landscape is not flat. The hard part with making such discoveries using evolutionary methods is that even if the landscape is not completely flat the positive and negative reinforcement needed to perform selection in such an environment almost always necessitates that the fitness function be crafted with this in mind by the researcher and few evolutionary programming researchers know anything about crypto. While there are a few strikes against such research (as the oft repeated "flat landscape" phrase shows) I would not let the current state of the art in this area disuade anyone interested. Most of the research done so far has been done by people who either knew little about crypto or little about evolutionary programming. There are also other areas of crypto relevance which may prove more amenable to evolutionary programming methods, like factoring... jim