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Synchronization of neural networks by mutual learning and its application to cryptography
Citation key Klein:2005:SNN
Author Einat Klein and Rachel Mislovaty and Ido Kanter and Andreas Ruttor and Wolfgang Kinzel
Title of Book Advances in Neural Information Processing Systems
Pages 689-696
Year 2005
Address Cambridge, MA
Volume 17
Editor L. K. Saul and Y. Weiss and L. Bottou
Publisher MIT Press
Abstract Two neural networks that are trained on their mutual output synchronize to an identical time dependant weight vector. This novel phenomenon can be used for creation of a secure cryptographic secret-key using a public channel. Several models for this cryptographic system have been suggested, and have been tested for their security under different sophisticated attack strategies. The most promising models are networks that involve chaos synchronization. The synchronization process of mutual learning is described analytically using statistical physics methods.
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