In the current digitalized world, cloud computing becomes a feasible solution for the virtualization of cloud computing resources. Though cloud computing has many advantages to outsourcing an organization’s information, but the strong security is the main aspect of cloud computing. Identity authentication theft becomes a vital part of the protection of cloud computing data. In this process, the intruders violate the security protocols and perform attacks on the organizations or user’s data. The situation of cloud data disclosure leads to the cloud user feeling insecure while using the cloud platform. The different traditional cryptographic techniques are not able to stop such kinds of attacks. BB84 protocol is the first quantum cryptography protocol developed by Bennett and Brassard in the year 1984. In the present work, three ways BB84GA security systems have been demonstrated using trusted cryptographic techniques like an attribute-based authentication system, BB84 protocol, and genetic algorithm. Firstly, attribute-based authentication is used for identity-based access control and thereafter BB84 protocol is used for quantum key distribution between both parties and later the concept of genetic algorithm is applied for encryption/decryption of sensitive information across the private/public clouds. The proposed concept of involvement of hybrid algorithms is highly secure and technologically feasible. It is a unique algorithm which may be used to minimize the security threats over the clouds. The computed results are presented in the form of tables and graphs.
The logistic regression model of the most important regression models a non-linear which aim getting estimators have a high of efficiency, taking character more advanced in the process of statistical analysis for being a models appropriate form of Binary Data.
Among the problems that appear as a result of the use of some statistical methods I
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Bivariate time series modeling and forecasting have become a promising field of applied studies in recent times. For this purpose, the Linear Autoregressive Moving Average with exogenous variable ARMAX model is the most widely used technique over the past few years in modeling and forecasting this type of data. The most important assumptions of this model are linearity and homogenous for random error variance of the appropriate model. In practice, these two assumptions are often violated, so the Generalized Autoregressive Conditional Heteroscedasticity (ARCH) and (GARCH) with exogenous varia
... Show MoreThis paper is concerned with preliminary test double stage shrinkage estimators to estimate the variance (s2) of normal distribution when a prior estimate of the actual value (s2) is a available when the mean is unknown , using specifying shrinkage weight factors y(×) in addition to pre-test region (R).
Expressions for the Bias, Mean squared error [MSE (×)], Relative Efficiency [R.EFF (×)], Expected sample size [E(n/s2)] and percentage of overall sample saved of proposed estimator were derived. Numerical results (using MathCAD program) and conclusions are drawn about selection of different constants including in the me
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Focused research aims to provide a framework cognitive analytical nature of real estate investments and how they evaluated in the light of the assessment tools of modern theory of real options, and the possibility to rely on that theory in the detection of the true value of projects, real estate investments that would maximize the value of the investment decision taken, and the analysis of those projects that arise in the real estate markets and environments is the organization, which she was to make sure cases and high-risk, compared with entrances techniques, discounted cash flow (net present value). Based on the assumption lies in the possibility of the application of the implic
... Show MoreIn this paper, estimation of system reliability of the multi-components in stress-strength model R(s,k) is considered, when the stress and strength are independent random variables and follows the Exponentiated Weibull Distribution (EWD) with known first shape parameter θ and, the second shape parameter α is unknown using different estimation methods. Comparisons among the proposed estimators through Monte Carlo simulation technique were made depend on mean squared error (MSE) criteria