Secure and linear cryptosystems using error-correcting codes

A public-key cryptosystem, digital signature and authentication procedures based on a Gallager-type parity-check error-correcting code are presented. The complexity of the encryption and the decryption processes scale linearly with the size of the plaintext Alice sends to Bob. The public-key is pre-corrupted by Bob, whereas a private-noise added by Alice to a given fraction of the ciphertext of each encrypted plaintext serves to increase the secure channel and is the cornerstone for digital signatures and authentication. Various scenarios are discussed including the possible actions of the opponent Oscar as an eavesdropper or as a disruptor

Secure exchange of information by synchronization of neural networks

A connection between the theory of neural networks and cryptography is presented. A new phenomenon, namely synchronization of neural networks is leading to a new method of exchange of secret messages. Numerical simulations show that two artificial networks being trained by Hebbian learning rule on their mutual outputs develop an antiparallel state of their synaptic weights. The synchronized weights are used to construct an ephemeral key exchange protocol for a secure transmission of secret data. It is shown that an opponent who knows the protocol and all details of any transmission of the data has no chance to decrypt the secret message, since tracking the weights is a hard problem compared to synchronization. The complexity of the generation of the secure channel is linear with the size of the network.Comment: 11 pages, 5 figure

Statistical mechanical aspects of joint source-channel coding

An MN-Gallager Code over Galois fields, $q$, based on the Dynamical Block Posterior probabilities (DBP) for messages with a given set of autocorrelations is presented with the following main results: (a) for a binary symmetric channel the threshold, $f_c$, is extrapolated for infinite messages using the scaling relation for the median convergence time, $t_{med} \propto 1/(f_c-f)$; (b) a degradation in the threshold is observed as the correlations are enhanced; (c) for a given set of autocorrelations the performance is enhanced as $q$ is increased; (d) the efficiency of the DBP joint source-channel coding is slightly better than the standard gzip compression method; (e) for a given entropy, the performance of the DBP algorithm is a function of the decay of the correlation function over large distances.Comment: 6 page

Do rBST-Free and Organic Milk Stigmatize Conventionally Produced Milk?

Producers are continually seeking to differentiate their products in the marketplace. A common approach is via labeling where differences in production methods are marketed. Yet, positive labeling for the new product has the potential to stigmatize the conventionally produced product by highlighting perceived problems with the product. The net economic result can be negative to producers as the conventional product that dominates the market is stigmatized by the new product that has little market share, and this leads to consumers decreasing their willingness to pay for the conventional product. This experimental research identifies this stigma effect in the case of milk, where the presentation of rBST-Free milk reduces consumers' willingness to purchase conventional milk.Demand and Price Analysis,

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.Comment: 4 page

Identifying Significant Characteristics of Organic Milk Consumers: A CART Analysis of an Artefactual Field Experiment

The organic dairy category is one the fastest growing categories of organic production in the U.S. Organic milk consumers generally cite perceived health benefits and lower risk of food contamination, as well as perceived superior quality and low environmental impact of organic farming methods, as the major motivations for preference of organic over conventional milk. While the properties of organic milk that are valued by consumers are fairly well-known, there is more ambiguity regarding the demographic characteristics of the typical organic milk consumer. This research makes use of experimental data and utilizes a relatively novel non-parametric modeling approach, the CART analysis, in identifying how willingness to pay for organic milk varies with the demographic profile of experiment participants. A more traditional econometric approach utilizing a Tobit regression is also performed to compare the results of the two models. The study finds that perceived taste of organic milk and concern for the risk of consuming conventional milk are major factors that separate experiment participants into groups with high and low WTP for organic milk.Consumer/Household Economics,