1,522 research outputs found
Interacting neural networks and cryptography
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
A Review on Biological Inspired Computation in Cryptology
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
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
Genetic attack on neural cryptography
Different scaling properties for the complexity of bidirectional
synchronization and unidirectional learning are essential for the security of
neural cryptography. Incrementing the synaptic depth of the networks increases
the synchronization time only polynomially, but the success of the geometric
attack is reduced exponentially and it clearly fails in the limit of infinite
synaptic depth. This method is improved by adding a genetic algorithm, which
selects the fittest neural networks. The probability of a successful genetic
attack is calculated for different model parameters using numerical
simulations. The results show that scaling laws observed in the case of other
attacks hold for the improved algorithm, too. The number of networks needed for
an effective attack grows exponentially with increasing synaptic depth. In
addition, finite-size effects caused by Hebbian and anti-Hebbian learning are
analyzed. These learning rules converge to the random walk rule if the synaptic
depth is small compared to the square root of the system size.Comment: 8 pages, 12 figures; section 5 amended, typos correcte
Authenticated tree parity machine key exchange
The synchronisation of Tree Parity Machines (TPMs), has proven to provide a
valuable alternative concept for secure symmetric key exchange. Yet, from a
cryptographer's point of view, authentication is at least as important as a
secure exchange of keys. Adding an authentication via hashing e.g. is
straightforward but with no relation to Neural Cryptography. We consequently
formulate an authenticated key exchange within this concept. Another
alternative, integrating a Zero-Knowledge protocol into the synchronisation, is
also presented. A Man-In-The-Middle attack and even all currently known
attacks, that are based on using identically structured TPMs and
synchronisation as well, can so be averted. This in turn has practical
consequences on using the trajectory in weight space. Both suggestions have the
advantage of not affecting the previously observed physics of this interacting
system at all.Comment: This work directly relates to cond-mat/0202112 (see also
http://arxiv.org/find/cond-mat/1/au:+Kinzel/0/1/0/all/0/1
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