Cryptographic Analysis of Random Sequences

Cryptographically strong random sequences are essential in cryptography, digital signatures, challenge-response systems, and in Monte Carlo simulation. This thesis examines techniques for cryptographic hardening of random sequences that are not cryptographically strong. Specific random sequences that are considered include d-sequences, that is sequences that are reciprocals of primes, and a new sequence obtained by the use of a specific two-dimensional mesh array. It is shown that the use of many-to-one mapping on blocks of the raw sequence improves the quality of autocorrelation function. Various types of many-to-one mappings are used and their effect on the autocorrelation function is compared. Sequences are also compared using another measure of randomness.Computer Science Departmen

Memory Storage in a Variable Threshold Artificial Neural Network

This thesis is concerned with the problem of memory storage in a feedback neural network. A new learning approach has been developed that assigns variable thresholds to the neurons through an iterative process. This approach has been further applied to B-Matrix approach of memory retrieval. Experiments have also been conducted on non-binary neural networks and their storage capacity has been evaluated.Computer Science Departmen