(American Institute of Science., 2015) Mulopa, John; Ndlovu, Siqabukile; Mzelikahle, Kernan; Nyathi, Thambo
Neural cryptography deals with the problem of key exchange between two communicating neural networks using the mutual
learning concept. It is the first algorithm for key generation over public channels which are not based on the number theory.
The two networks exchange their outputs and the key between the two communicating parties is eventually presented in the
final learned weights, when the two networks are synchronised. The security of neural synchronisation is put at risk if an
attacker is capable of synchronising with any of the two parties during the training processes. However, the security of a
cryptosystem is robust if the algorithm is strong and the keys are long, unpredictable, and random This research proposes use
of two distant remote Adaptive Resonance Theory MAP (ARTMAP) architectures that are trained to learn from a unique data
set and finally synchronise to same weights.