Physics – Condensed Matter – Disordered Systems and Neural Networks
Scientific paper
2004-11-15
J. Stat. Mech. (2005) P01009
Physics
Condensed Matter
Disordered Systems and Neural Networks
12 pages, 8 figures; typos corrected
Scientific paper
10.1088/1742-5468/2005/01/P01009
Neural cryptography is based on synchronization of tree parity machines by mutual learning. We extend previous key-exchange protocols by replacing random inputs with queries depending on the current state of the neural networks. The probability of a successful attack is calculated for different model parameters using numerical simulations. The results show that queries restore the security against cooperating attackers. The success probability can be reduced without increasing the average synchronization time.
Kanter Ido
Kinzel Wolfgang
Ruttor Andreas
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