Symmetric cryptography forms the backbone of secure data communication and storage by relying on the strength and randomness of cryptographic keys. This increases complexity, enhances cryptographic systems' overall robustness, and is immune to various attacks. The present work proposes a hybrid model based on the Latin square matrix (LSM) and subtractive random number generator (SRNG) algorithms for producing random keys. The hybrid model enhances the security of the cipher key against different attacks and increases the degree of diffusion. Different key lengths can also be generated based on the algorithm without compromising security. It comprises two phases. The first phase generates a seed value that depends on producing a randomly predefined set of key numbers of size n via the Donald E. Knuths SRNG algorithm (subtractive method). The second phase uses the output key (or seed value) from the previous phase as input to the Latin square matrix (LSM) to formulate a new key randomly. To increase the complexity of the generated key, another new random key of the same length that fulfills Shannon’s principle of confusion and diffusion properties is XORed. Four test keys for each 128, 192,256,512, and 1024–bit length are used to evaluate the strength of the proposed model. The experimental results and security analyses revealed that all test keys met the statistical National Institute of Standards (NIST) standards and had high values for entropy values exceeding 0.98. The key length of the proposed model for n bits is 25*n, which is large enough to overcome brute-force attacks. Moreover, the generated keys are very sensitive to initial values, which increases the complexity against different attacks.
The absence of ecological perception in the local urbanization resulted in the lack of a clear conception of achieving sustainability in its simplest form in the urban reality and in the city of Baghdad in particular. The research assumes the possibility of achieving urban sustainability in Iraqi cities by applying the cities for the most effective methods to implemented ecological solutions and introducing appropriate urban planning tools and improve the living environment. The research focuses on the ability to define some aspects to achieve a sustainable local urban identity from global experiences. This was performed by proposing a scheduled theoretical framework, through which the features of sustainability can be extrapolated from the
... Show MoreThe research aims to determine the mix of production optimization in the case of several conflicting objectives to be achieved at the same time, therefore, discussions dealt with the concept of programming goals and entrances to be resolved and dealt with the general formula for the programming model the goals and finally determine the mix of production optimization using a programming model targets to the default case.
The absence of ecological perception in the local urbanization resulted in the lack of a clear conception of achieving sustainability in its simplest form in the urban reality and in the city of Baghdad in particular. The research assumes the possibility of achieving urban sustainability in Iraqi cities by applying the cities for the most effective methods to implemented ecological solutions and introducing appropriate urban planning tools and improve the living environment. The research focuses on the ability to define some aspects to achieve a sustainable local urban identity from global experiences. This was performed by proposing a scheduled theoretical framework, through which th
The logistic regression model is one of the oldest and most common of the regression models, and it is known as one of the statistical methods used to describe and estimate the relationship between a dependent random variable and explanatory random variables. Several methods are used to estimate this model, including the bootstrap method, which is one of the estimation methods that depend on the principle of sampling with return, and is represented by a sample reshaping that includes (n) of the elements drawn by randomly returning from (N) from the original data, It is a computational method used to determine the measure of accuracy to estimate the statistics, and for this reason, this method was used to find more accurate estimates. The ma
... Show MoreJob stress is considered one of the most important obstacles that may appear in the work field. In order to deal with the obstacles and challenges , the idea to deal with job stress has come to address job stress as one of the most important trends that enable organizations to face those challenges through focusing on the role of job stress and the organizational climate of the organization.
The research deals with two variables: the job stress as an independent variable, and the organizational climate as a dependent one. Each variable includes five sub-dimensions. These dimensions have been involved in an interaction to form
... Show MoreThe parametric programming considered as type of sensitivity analysis. In this research concerning to study the effect of the variations on linear programming model (objective function coefficients and right hand side) on the optimal solution. To determine the parameter (θ) value (-5≤ θ ≤5).Whereas the result، the objective function equal zero and the decision variables are non basic، when the parameter (θ = -5).The objective function value increases when the parameter (θ= 5) and the decision variables are basic، with the except of X24, X34.Whenever the parameter value increase, the objectiv
... Show MoreIn this research The study of Multi-level model (partial pooling model) we consider The partial pooling model which is one Multi-level models and one of the Most important models and extensive use and application in the analysis of the data .This Model characterized by the fact that the treatments take hierarchical or structural Form, in this partial pooling models, Full Maximum likelihood FML was used to estimated parameters of partial pooling models (fixed and random ), comparison between the preference of these Models, The application was on the Suspended Dust data in Iraq, The data were for four and a half years .Eight stations were selected randomly among the stations in Iraq. We use Akaik′s Informa
... Show MoreIn this research The study of Multi-level model (partial pooling model) we consider The partial pooling model which is one Multi-level models and one of the Most important models and extensive use and application in the analysis of the data .This Model characterized by the fact that the treatments take hierarchical or structural Form, in this partial pooling models, Full Maximum likelihood FML was used to estimated parameters of partial pooling models (fixed and random ), comparison between the preference of these Models, The application was on the Suspended Dust data in Iraq, The data were for four and a half years .Eight stations were selected randomly among the stations in Iraq. We use Akaik′s Informa
... Show MoreIn this paper an estimator of reliability function for the pareto dist. Of the first kind has been derived and then a simulation approach by Monte-Calro method was made to compare the Bayers estimator of reliability function and the maximum likelihood estimator for this function. It has been found that the Bayes. estimator was better than maximum likelihood estimator for all sample sizes using Integral mean square error(IMSE).