Merging biometrics with cryptography has become more familiar and a great scientific field was born for researchers. Biometrics adds distinctive property to the security systems, due biometrics is unique and individual features for every person. In this study, a new method is presented for ciphering data based on fingerprint features. This research is done by addressing plaintext message based on positions of extracted minutiae from fingerprint into a generated random text file regardless the size of data. The proposed method can be explained in three scenarios. In the first scenario the message was used inside random text directly at positions of minutiae in the second scenario the message was encrypted with a choosen word before ciphering inside random text. In the third scenario the encryption process insures a correct restoration of original message. Experimental results show that the proposed cryptosystem works well and secure due to the huge number of fingerprints may be used by attacker to attempt message extraction where all fingerprints but one will give incorrect results and the message will not represent original plain-text, also this method ensures that any intended tamper or simple damage will be discovered due to failure in extracting proper message even if the correct fingerprint are used.
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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 rand
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User confidentiality protection is concerning a topic in control and monitoring spaces. In image, user's faces security in concerning with compound information, abused situations, participation on global transmission media and real-world experiences are extremely significant. For minifying the counting needs for vast size of image info and for minifying the size of time needful for the image to be address computationally. consequently, partial encryption user-face is picked. This study focuses on a large technique that is designed to encrypt the user's face slightly. Primarily, dlib is utilizing for user-face detection. Susan is one of the top edge detectors with valuable localization characteristics marked edges, is used to extract
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The electrospun nanofibers membranes (ENMs) have gained great attention due to their superior performance. However, the low mechanical strength of ENMs, such as the rigidity and low strength, limits their applications in many aspects which need adequate strength, such as water filtration. This work investigates the impact of electrospinning parameters on the properties of ENMs fabricated from polyacrylonitrile (PAN) solved in N, N-Dimethylformamide (DMF). The studied electrospinning parameters were polymer concentration, solution flow rate, collector rotating speed, and the distance between the needle and collector. The fabricated ENMs were characterized using scanning electron microscopy (SEM) to understand the surface morphology and es
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The advancement of cement alternatives in the construction materials industry is fundamental to sustainable development. Geopolymer is the optimal substitute for ordinary Portland cement, which produces 80% less CO2 emissions than ordinary Portland cement. Metakaolin was used as one of the raw materials in the geopolymerization process. This research examines the influence of three different percentages of sulfate (0.00038, 1.532, and 16.24) % in sand per molarity of NaOH on the compressive strength of metakaolin-based geopolymer mortar (MK-GPM). Samples were prepared with two different molarities (8M and 12M) and cured at room temperature. The best compressive strength value (56.98MPa) was recorded with 12M w
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In this paper, we consider a new approach to solve type of partial differential equation by using coupled Laplace transformation with decomposition method to find the exact solution for non–linear non–homogenous equation with initial conditions. The reliability for suggested approach illustrated by solving model equations such as second order linear and nonlinear Klein–Gordon equation. The application results show the efficiency and ability for suggested approach.
In this research the Empirical Bayes method is used to Estimate the affiliation parameter in the clinical trials and then we compare this with the Moment Estimates for this parameter using Monte Carlo stimulation , we assumed that the distribution of the observation is binomial distribution while the distribution with the unknown random parameters is beta distribution ,finally we conclude that the Empirical bayes method for the random affiliation parameter is efficient using Mean Squares Error (MSE) and for different Sample size .
In this research, the Williamson-Hall method and of size-strain plot method was employed to analyze X- ray lines for evaluating the crystallite size and lattice strain and of cadmium oxide nanoparticles. the crystallite size value is (15.2 nm) and (93.1 nm) and lattice strain (4.2 x10−4 ) and (21x10−4) respectively. Also, other methods have been employed to evaluate the crystallite size. The current methods are (Sherrer and modified Sherrer methods ) and their results are (14.8 nm) and (13.9nm) respectively. Each method of analysis has a different result because the alteration in the crystallite size and lattice strain calculated according to the Williamson-Hall and size-strain plot methods shows that the non-uniform strain in nan
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