منابع مشابه
Neural cryptography with queries
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 agai...
متن کاملNeural Cryptography
Two neural networks which are trained on their mutual output bits show a novel phenomenon: The networks synchronize to a state with identical time dependent weights. It is shown how synchronization by mutual learning can be applied to cryptography: secret key exchange over a public channel.
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In this paper we analyse the security of a new key exchange protocol proposed in [3], which is based on mutually learning neural networks. This is a new potential source for public key cryptographic schemes which are not based on number theoretic functions, and have small time and memory complexities. In the first part of the paper we analyse the scheme, explain why the two parties converge to ...
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In this paper, neural network based cryptology is performed. The system consists of two stages. In the first stage, neural network-based pseudo-random numbers (NPRNGs) are generated and the results are tested for randomness using National Institute of Standard Technology (NIST) randomness tests. In the second stage, a neural network-based cryptosystem is designed using NPRNGs. In this cryptosys...
متن کاملNeural synchronization and cryptography
Neural networks can synchronize by learning from each other. For that purpose they receive common inputs and exchange their outputs. Adjusting discrete weights according to a suitable learning rule then leads to full synchronization in a finite number of steps. It is also possible to train additional neural networks by using the inputs and outputs generated during this process as examples. Seve...
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ژورنال
عنوان ژورنال: Physical Review E
سال: 2004
ISSN: 1539-3755,1550-2376
DOI: 10.1103/physreve.69.046110