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.
Objectives: Osteoporosis (OP) is a systemic skeletal disorder characterized with bone mass loss and microstructure, resulting in fragility fractures. Continued secretion of Osteopontin (OPN), osteonectin (ON), osteocalcin (OCN), Parathyroid hormone (PTH) and Ca+2 lead to bone remodeling disorders, followed by bone loss and osteoporosis (OP). The current study aims to investigate the biochemical proteins OPN, OCN, and ON in postmenopausal women with osteoporosis and determine whether we could use them as good indicators for OP diagnostics. Materials and Methods: Case- control study carried out between December 2022 and July 2023. OP disease was confirmed among 108 Iraqi postmenopausal women randomly selected from different Iraqi hospitals, B
... Show MoreThe Life Cycle and Larval Development of Neoechinorhynchus iraqensis (Acanthocephala: Neoechinorhynchidae) in the Intermediate Host
The study seeks to analyze the perceptions of audience in UAE towards the performance of Emirates Satellite TV Channels. It analyzed the exposure motivations of audience to satellite TV channels, its positive and negative aspects and to what extent they abide by media ethics. A survey is conducted with a sample of four hundred. The study shows significant differences between male and female towards the characteristics of TV channels, its positive and negative aspects and its commitments to media ethics.
The study also shows that the expectancy value model and third person effect model are applicable in studying the perceptions of audience and media people in UAE t
... Show MoreMost of the studies conducted in the past decades focused on the effect of interest rates and exchange rates on domestic investment under the assumption that the independent variables have the same effect on the dependent variable, but there were limited studies that investigated the unequal effects of changes in interest rates and exchange rates, both positive and negative, on domestic investment. This study used a nonlinear autoregressive distributed lag (NARDL) model to assess the unequal effects of the real interest rate and real exchange rate variables on domestic investment in Egypt for the period 1976 - 2020. The results revealed that positive and negative shocks for both exchange rates have unequal effects on
... Show MoreThe study aimed to evaluate the level of MMP‑2 in acute myeloid leukemia (AML) patients in comparison with that in remission status, and healthy subjects, and to find its correlation with hematologic parameters. This study included sixty newly diagnosed AML patients. Remission status was assessed after induction chemotherapy. The overall survival (OS) was determined after 6 months. The plasma MMP‑2 level was measured at diagnosis by enzyme immunoassay. Twenty‑eight healthy individuals were recruited as a control group. Plasma MMP‑2 was higher in AML patients than in healthy individuals (P = 0.005). The level of MMP‑2 was much higher in the M5 subtype than in the other subtypes (P = 0.0001). There was no statistically significant d
... Show MoreBackground: As a multifactorial disorder, temporomandibular joint (TMD) is difficult to diagnose, and multiple factors affect the joint and cause the temporomandibular disorder. Standardization of clinical diagnosis of TMD should be used to reach a definite clinical diagnosis; the condylar bone may degenerate in accordance with these disorders. Aims: Evaluate the correlation between the clinical diagnosis and degenerative condylar change (flattening, sclerosis, erosion, and osteophyte). Materials and Methods: A prospective study with a study group of 97 TMD patients (total of 194 joints) aged 20 to 50. Patients were sent to cone beam computed tomography (CBCT) to assess the degenerative condylar change. Results: No association was found bet
... Show MoreFinger vein recognition and user identification is a relatively recent biometric recognition technology with a broad variety of applications, and biometric authentication is extensively employed in the information age. As one of the most essential authentication technologies available today, finger vein recognition captures our attention owing to its high level of security, dependability, and track record of performance. Embedded convolutional neural networks are based on the early or intermediate fusing of input. In early fusion, pictures are categorized according to their location in the input space. In this study, we employ a highly optimized network and late fusion rather than early fusion to create a Fusion convolutional neural network
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