Neural cryptography with queries

Physics – Condensed Matter – Disordered Systems and Neural Networks

Scientific paper

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Details

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.

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