Public-channel cryptography using chaos synchronization.

We present a key-exchange protocol that comprises two parties with chaotic dynamics that are mutually coupled and undergo a synchronization process, at the end of which they can use their identical dynamical state as an encryption key. The transferred coupling- signals are based nonlinearly on time-delayed states of the parties, and therefore they conceal the parties' current state and can be transferred over a public channel. Synchronization time is linear in the number of synchronized digits alpha, while the probability for an attacker to synchronize with the parties drops exponentially with alpha. To achieve security with finite alpha we use a network.

Cooperating attackers in neural cryptography.

A successful attack strategy in neural cryptography is presented. The neural cryptosystem, based on synchronization of neural networks by mutual learning, has been recently shown to be secure under different attack strategies. The success of the advanced attacker presented here, called the "majority-flipping attacker," does not decay with the parameters of the model. This attacker's outstanding success is due to its using a group of attackers which cooperate throughout the synchronization process, unlike any other attack strategy known. An analytical description of this attack is also presented, and fits the results of simulations.

Public channel cryptography by synchronization of neural networks and chaotic maps.

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.