Today, the role of cloud computing in our day-to-day lives is very prominent. The cloud computing paradigm makes it possible to provide demand-based resources. Cloud computing has changed the way that organizations manage resources due to their robustness, low cost, and pervasive nature. Data security is usually realized using different methods such as encryption. However, the privacy of data is another important challenge that should be considered when transporting, storing, and analyzing data in the public cloud. In this paper, a new method is proposed to track malicious users who use their private key to decrypt data in a system, share it with others and cause system information leakage. Security policies are also considered to be integrated with the texts encrypted to ensure system safety and to prevent the violation of data owners ' privacy. For this purpose, before sending the data to the cloud, it must be encrypted in such a way that operations such as max, min, etc. can be performed on it. The proposed method uses order-preserving symmetric encryption (OPES), which does not require decryption or re-encryption for mathematical operations. This process leads to a great improvement in delay. The OPES scheme allows comparison operations to be performed directly on encrypted data without decryption operands. According to the results, it is obvious that the proposed strategy is in a better position compared to the base paper in terms of the system's ability to find the malicious elements that cause the problem of leakage and in terms of system security to prevent the violation of privacy.
Use Almtafr Alcderan orange, one of the factors Hashr Alttafaria to study Alatjabh isolates elected on the basis of specifications so that was a positive response with mutagen record and system consisting of three isolates used Alcderan orange graded concentrations and under specific Trov similar conditions Alttafar Pal NTG compared
In this study, silver-tungsten oxide core–shell nanoparticles (Ag–WO3 NPs) were synthesized by pulsed laser ablation in liquid employing a (1.06 µm) Q-switched Nd:YAG laser, at different Ag colloidal concentration environment (different core concentration). The produced Ag–WO3 core–shell NPs were subjected to characterization using UV–visible spectrophotometry, X-ray diffraction (XRD), transmission electron microscopy (TEM), energy-dispersive spectroscopy, electrical analysis, and photoluminescence PL. The UV–visible spectra exhibited distinct absorption peaks at around 200 and 405 nm, which attributed to the occurrence of surface Plasmon reson
The aim of the present research is to know the following : What are the Science and technology, society and environment issues (S.T.S.E) which included in the content of thechemistry Book second grade intermediate ? And to achieve the objective of search The two researchers has prepares a list of science and technology, society and environment issues (STSE) consisted of (9) key issues namely (Air quality and the atmosphere, sustainable development, water security, health and preventive security, mineral resources investment, pollution of various kinds, energy, food industry, production of weapons technology) and from which (70) sub-issues emerge,Arbitrators competent agreement has been received . Then, thetwo researchers analyzed the con
... Show MoreEmpirical and statistical methodologies have been established to acquire accurate permeability identification and reservoir characterization, based on the rock type and reservoir performance. The identification of rock facies is usually done by either using core analysis to visually interpret lithofacies or indirectly based on well-log data. The use of well-log data for traditional facies prediction is characterized by uncertainties and can be time-consuming, particularly when working with large datasets. Thus, Machine Learning can be used to predict patterns more efficiently when applied to large data. Taking into account the electrofacies distribution, this work was conducted to predict permeability for the four wells, FH1, FH2, F
... Show MoreAccurate predictive tools for VLE calculation are always needed. A new method is introduced for VLE calculation which is very simple to apply with very good results compared with previously used methods. It does not need any physical property except each binary system need tow constants only. Also, this method can be applied to calculate VLE data for any binary system at any polarity or from any group family. But the system binary should not confirm an azeotrope. This new method is expanding in application to cover a range of temperature. This expansion does not need anything except the application of the new proposed form with the system of two constants. This method with its development is applied to 56 binary mixtures with 1120 equili
... Show MoreAttacking a transferred data over a network is frequently happened millions time a day. To address this problem, a secure scheme is proposed which is securing a transferred data over a network. The proposed scheme uses two techniques to guarantee a secure transferring for a message. The message is encrypted as a first step, and then it is hided in a video cover. The proposed encrypting technique is RC4 stream cipher algorithm in order to increase the message's confidentiality, as well as improving the least significant bit embedding algorithm (LSB) by adding an additional layer of security. The improvement of the LSB method comes by replacing the adopted sequential selection by a random selection manner of the frames and the pixels wit
... Show MoreThe seasonal behavior of the light curve for selected star SS UMI and EXDRA during outburst cycle is studied. This behavior describes maximum temperature of outburst in dwarf nova. The raw data has been mathematically modeled by fitting Gaussian function based on the full width of the half maximum and the maximum value of the Gaussian. The results of this modeling describe the value of temperature of the dwarf novae star system leading to identify the type of elements that each dwarf nova consisted of.
Traffic classification is referred to as the task of categorizing traffic flows into application-aware classes such as chats, streaming, VoIP, etc. Most systems of network traffic identification are based on features. These features may be static signatures, port numbers, statistical characteristics, and so on. Current methods of data flow classification are effective, they still lack new inventive approaches to meet the needs of vital points such as real-time traffic classification, low power consumption, ), Central Processing Unit (CPU) utilization, etc. Our novel Fast Deep Packet Header Inspection (FDPHI) traffic classification proposal employs 1 Dimension Convolution Neural Network (1D-CNN) to automatically learn more representational c
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