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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.