Mutual Information, Strange Attractors, and the Optimal Estimation of Dimension

It has been shown that the appropriate setting of data windows is crucial to a successful estimation of a time-series correlation dimension using the Grassberger-Procaccia algorithm [Physica 9D, 189 (1983); Phys. Rev. Lett. 50, 346 (1983)], and it has been proposed that the first minimum of the corresponding mutual-information function may be an appropriate window value. We have tested this hypothesis against data generated by the Rossler equations, the Lorenz equations, and a three-dimensional irrational torus. We conclude that mutual information is not consistently successful in identifying the optimal window

Evaluation of alternative discrete-event simulation experimental methods

The aim of the research was to assist non-experts produce meaningful, non-terminating discrete event simulations studies. The exemplar used was manufacturing applications, in particular sequential production lines. The thesis addressed the selection of methods for introducing randomness, setting the length of individual simulation runs, and determining the conditions for starting measurements". Received wisdom" in these aspects of simulation experimentation was not accepted.The research made use of a Markov Chain queuing model and statistica analysis of exhaustive computer-based experimentation using test models. A specific production-line model drawn from the motor industry was used as a point of reference. A distinctive,quality control like, process of facilitating the controlled introduction of "representative randomness" from a pseudo random-number generator was developed, rather than relying on a generator's a priori performance in standard statistical tests of randomness. This approach proved to be effective and practical. Other results included: The distortion in measurements due to the initial conditions of a simulation run of a queue was only corrected by a lengthy run and not by discarding early results. Simulation experiments of the same queue, demonstrated that a single long run gave greater accuracy than having multiple runs. The choice of random number generator is less important than the choice of seed. Notably, RANDU (a "discredited"MLCG) with careful seed selection was able to outperform in tests both real random numbers, and other MLCGs if their seed were chosen randomly,99.8% of the time. Similar results were obtained for Mersenne Twister and Descriptive Sampling.Descriptive Samnpling was found to provide the best samples and was less susceptible to errorsin the forecast of the required sample size. A method of determining the run length of the simulation that would ensure the run was representative of the true condifions was proposed. An interactive computer program was created to assist in the calculation of the run length of a simulation and determine seeds so as to obtain" highly representative" samples, demonstrating the facility required in simulation software to support theses elected methods

User-controlled cyber-security using automated key generation

Traditionally, several different methods are fully capable of providing an adequate degree of security to the threats and attacks that exists for revealing different keys. Though almost all the traditional methods give a good level of immunity to any possible breach in security keys, the biggest issue that exist with these methods is the dependency over third-party applications. Therefore, use of third-party applications is not an acceptable method to be used by high-security applications. For high-security applications, it is more secure that the key generation process is in the hands of the end users rather than a third-party. Giving access to third parties for high-security applications can also make the applications more venerable to data theft, security breach or even a loss in their integrity. In this research, the evolutionary computing tool Eureqa is used for the generation of encryption keys obtained by modelling pseudo-random input data. Previous approaches using this tool have required a calculation time too long for practical use and addressing this drawback is the main focus of the research. The work proposes a number of new approaches to the generation of secret keys for the encryption and decryption of data files and they are compared in their ability to operate in a secure manner using a range of statistical tests and in their ability to reduce calculation time using realistic practical assessments. A number of common tests of performance are the throughput, chi-square, histogram, time for encryption and decryption, key sensitivity and entropy analysis. From the results of the statistical tests, it can be concluded that the proposed data encryption and decryption algorithms are both reliable and secure. Being both reliable and secure eliminates the need for the dependency over third-party applications for the security keys. It also takes less time for the users to generate highly secure keys compared to the previously known techniques.The keys generated via Eureqa also have great potential to be adapted to data communication applications which require high security

Tethered Monte Carlo: computing the effective potential without critical slowing down

We present Tethered Monte Carlo, a simple, general purpose method of computing the effective potential of the order parameter (Helmholtz free energy). This formalism is based on a new statistical ensemble, closely related to the micromagnetic one, but with an extended configuration space (through Creutz-like demons). Canonical averages for arbitrary values of the external magnetic field are computed without additional simulations. The method is put to work in the two dimensional Ising model, where the existence of exact results enables us to perform high precision checks. A rather peculiar feature of our implementation, which employs a local Metropolis algorithm, is the total absence, within errors, of critical slowing down for magnetic observables. Indeed, high accuracy results are presented for lattices as large as L=1024.Comment: 32 pages, 8 eps figures. Corrected Eq. (36), which is wrong in the published pape

Evaluation of alternative discrete-event simulation experimental methods

The aim of the research was to assist non-experts produce meaningful, non-terminating discrete event simulations studies. The exemplar used was manufacturing applications, in particular sequential production lines. The thesis addressed the selection of methods for introducing randomness, setting the length of individual simulation runs, and determining the conditions for starting measurements". Received wisdom" in these aspects of simulation experimentation was not accepted.The research made use of a Markov Chain queuing model and statistica analysis of exhaustive computer-based experimentation using test models. A specific production-line model drawn from the motor industry was used as a point of reference. A distinctive,quality control like, process of facilitating the controlled introduction of "representative randomness" from a pseudo random-number generator was developed, rather than relying on a generator's a priori performance in standard statistical tests of randomness. This approach proved to be effective and practical. Other results included: The distortion in measurements due to the initial conditions of a simulation run of a queue was only corrected by a lengthy run and not by discarding early results. Simulation experiments of the same queue, demonstrated that a single long run gave greater accuracy than having multiple runs. The choice of random number generator is less important than the choice of seed. Notably, RANDU (a "discredited"MLCG) with careful seed selection was able to outperform in tests both real random numbers, and other MLCGs if their seed were chosen randomly,99.8% of the time. Similar results were obtained for Mersenne Twister and Descriptive Sampling.Descriptive Samnpling was found to provide the best samples and was less susceptible to errorsin the forecast of the required sample size. A method of determining the run length of the simulation that would ensure the run was representative of the true condifions was proposed. An interactive computer program was created to assist in the calculation of the run length of a simulation and determine seeds so as to obtain" highly representative" samples, demonstrating the facility required in simulation software to support theses elected methods.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

New Classes of Binary Random Sequences for Cryptography

In the vision for the 5G wireless communications advancement that yield new security prerequisites and challenges we propose a catalog of three new classes of pseudorandom random sequence generators. This dissertation starts with a review on the requirements of 5G wireless networking systems and the most recent development of the wireless security services applied to 5G, such as private-keys generation, key protection, and flexible authentication. This dissertation proposes new complexity theory-based, number-theoretic approaches to generate lightweight pseudorandom sequences, which protect the private information using spread spectrum techniques. For the class of new pseudorandom sequences, we obtain the generalization. Authentication issues of communicating parties in the basic model of Piggy Bank cryptography is considered and a flexible authentication using a certified authority is proposed

Spectral analysis of random number generators

This paper is based on the theory developed by Dr. Evangelos Yfantis, professor of Computer Science at University of Nevada, Las Vegas. In this paper, we describe a method for testing the fairness of pseudorandom number generators using the Discrete Fourier Transform. We will show how the concept of a random process can be used in a representation for random discrete time signals. Using this concept, we have focused on the mathematical representations of the spectral analysis of a fair pseudorandom number generator. From this representation, a reasonable spectral expectation is determined. An algorithm which applies the developed method is described, and a modified shift register random number generator is used to produce sample data