Public channel cryptography by synchronization of neural networks and chaotic maps

Abstract

Two different kinds of synchronization have been applied to cryptography: Synchronization of chaotic maps by one common external signal and synchronization of neural networks by mutual learning. By combining these two mechanisms, where the external signal to the chaotic maps is synchronized by the nets, we construct a hybrid network which allows a secure generation of secret encryption keys over a public channel. The security with respect to attacks, recently proposed by Shamir et al, is increased by chaotic synchronization.

4 pages

References in corpus (3)

• Secure exchange of information by synchronization of neural networks
• Mutual learning in a tree parity machine and its application to cryptography
• A secure key-exchange protocol with an absence of injective functions

Cited by in corpus (13)

• Genetic attack on neural cryptography
• Transient Uncoupling Induces Synchronization
• Dynamics of neural cryptography
• Cooperating Attackers in Neural Cryptography
• Neural cryptography with feedback
• Comment on novel public key encryption technique based on multiple chaotic systems
• Replica theory for Levy spin glasses
• Neural Synchronization and Cryptography
• Successful attack on permutation-parity-machine-based neural cryptography
• Image Authentication Based on Neural Networks
• Optimization of the Asymptotic Property of Mutual Learning Involving an Integration Mechanism of Ensemble Learning
• Breaking a chaotic image encryption algorithm based on perceptron model
• Tree Parity Machine Rekeying Architectures