7,740 research outputs found

    Using Echo State Networks for Cryptography

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    Echo state networks are simple recurrent neural networks that are easy to implement and train. Despite their simplicity, they show a form of memory and can predict or regenerate sequences of data. We make use of this property to realize a novel neural cryptography scheme. The key idea is to assume that Alice and Bob share a copy of an echo state network. If Alice trains her copy to memorize a message, she can communicate the trained part of the network to Bob who plugs it into his copy to regenerate the message. Considering a byte-level representation of in- and output, the technique applies to arbitrary types of data (texts, images, audio files, etc.) and practical experiments reveal it to satisfy the fundamental cryptographic properties of diffusion and confusion.Comment: 8 pages, ICANN 201

    A Review on Biological Inspired Computation in Cryptology

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    Cryptology is a field that concerned with cryptography and cryptanalysis. Cryptography, which is a key technology in providing a secure transmission of information, is a study of designing strong cryptographic algorithms, while cryptanalysis is a study of breaking the cipher. Recently biological approaches provide inspiration in solving problems from various fields. This paper reviews major works in the application of biological inspired computational (BIC) paradigm in cryptology. The paper focuses on three BIC approaches, namely, genetic algorithm (GA), artificial neural network (ANN) and artificial immune system (AIS). The findings show that the research on applications of biological approaches in cryptology is minimal as compared to other fields. To date only ANN and GA have been used in cryptanalysis and design of cryptographic primitives and protocols. Based on similarities that AIS has with ANN and GA, this paper provides insights for potential application of AIS in cryptology for further research

    Tree Parity Machine Rekeying Architectures

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    The necessity to secure the communication between hardware components in embedded systems becomes increasingly important with regard to the secrecy of data and particularly its commercial use. We suggest a low-cost (i.e. small logic-area) solution for flexible security levels and short key lifetimes. The basis is an approach for symmetric key exchange using the synchronisation of Tree Parity Machines. Fast successive key generation enables a key exchange within a few milliseconds, given realistic communication channels with a limited bandwidth. For demonstration we evaluate characteristics of a standard-cell ASIC design realisation as IP-core in 0.18-micrometer CMOS-technology

    Cryptanalysis of two chaotic encryption schemes based on circular bit shift and XOR operations

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    Recently two encryption schemes were proposed by combining circular bit shift and XOR operations, under the control of a pseudorandom bit sequence (PRBS) generated from a chaotic system. This paper studies the security of these two encryption schemes and reports the following findings: 1) there exist some security defects in both schemes; 2) the underlying chaotic PRBS can be reconstructed as an equivalent key by using only two chosen plaintexts; 3) most elements in the underlying chaotic PRBS can be obtained by a differential known-plaintext attack using only two known plaintexts. Experimental results are given to demonstrate the feasibility of the proposed attack.Comment: 17 pages, 8 figure

    Interacting neural networks and cryptography

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    Two neural networks which are trained on their mutual output bits are analysed using methods of statistical physics. The exact solution of the dynamics of the two weight vectors shows a novel phenomenon: The networks synchronize to a state with identical time dependent weights. Extending the models to multilayer networks with discrete weights, it is shown how synchronization by mutual learning can be applied to secret key exchange over a public channel.Comment: Invited talk for the meeting of the German Physical Societ
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