Neural network identification of keystream generators
Leader, Jeffery J.
Heyman, James E.
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Applications such as stream ciphers and spread spectra require the generation of binary keystreams to implement, and the simulation of such keystreams to break. Most cryptanalytic attacks are of the known generator type, that is, they assume knowledge of the method used to generate the keystream. We show that a neural network can be used to identify the generator, and in some cases to simulate the keystream.