In this paper, the botnet detection problem is defined as a feature selection problem and the genetic algorithm (GA) is used to search for the best significant combination of features from the entire search space of set of features. Furthermore, the Decision Tree (DT) classifier is used as an objective function to direct the ability of the proposed GA to locate the combination of features that can correctly classify the activities into normal traffics and botnet attacks. Two datasets namely the UNSW-NB15 and the Canadian Institute for Cybersecurity Intrusion Detection System 2017 (CICIDS2017), are used as evaluation datasets. The results reveal that the proposed DT-aware GA can effectively find the relevant features from the whole features set. Thus, it obtains efficient botnet detection results in terms of F-score, precision, detection rate, and number of relevant features, when compared with DT alone.
Background: Multiple sclerosis (MS) is a chronic neurodegenerative autoimmune disease mediated by autoreactive T cells against myelin-basic proteins. Cytokines are suggested to play a role in the etiopathogenesis of the disease. Among these cytokines is interleukin-2 (IL-2). Aim of the study: To investigate the association between IL2+166 G/T single nucleotide polymorphism (SNP: rs2069763) and MS in Iraqi patients. Serum level of IL-2 was also detected. Anti-rubella IgG antibody was further determined in the sera of patients. Patients and methods: Eighty MS patients (28 males and 52 females; age mean ± SD: 39.2 ± 16.1 years) and 80 healthy control matched patients for age (32.15 ± 16.13 years) and gender (28 males and 52 females) were en
... Show MoreBackground: The genetic polymorphisms of vitamin D receptor (VDR) have an association with thalassemia development, additionally to the environmental elements that elicited the disorder in the genetically predisposed individuals. As well, VDR functions responsible for the regulation of bone metabolism, such its part in immunity. Aim: The sitting study intended to inspect the association between thalassemia disease and the genetic polymorphisms of VDR among the Iraqi population then compared these findings to other findings of thalassemia patients in other different ethnic populations. Materials and methods: The restriction enzymes Bsm-I and Fok-I were applied to determine the genetic polymorphisms frequencies of VDR by a Polymerase Chain Re
... Show MoreObjective: To assess the role of tumour necrosis factor alpha level and genotyping in susceptibility to leishmaniasis.Method: The case-control study was conducted from March to July 2021 at Baqubah Teaching Hospital, Diyala, Iraq,and comprised patients of cutaneous leishmaniasis in group A and healthy controls in group B. The serum level andsingle nucleotide polymorphisms of tumour necrosis factor-alpha rs41297589 and rs1800629 were compared betweenthe groups. Data was analysed using SPSS 28.Results: Of the 150 subjects, there were 75(50%) in group A; 39(52%) males and 36(48%) females with mean age23.91±13.14 years. The remaining 75(50%) subjects were in group B; 38(50.7%) males and 37(49.3%) females withmean age 22.84±4.35 years.
... Show MoreBackground: Hypothyroidism is the most abundant thyroid disorder worldwide. For decades, levothyroxine was the main effective pharmacological treatment for hypothyroidism. A variety of factors can influence levothyroxine dose, such as genetic variations. Studying the impact of genetic polymorphisms on the administration of medications was risen remarkably. Different genetic variations were investigated that might affect levothyroxine dose requirements, especially the deiodinase enzymes. Deiodinase type 2 genetic polymorphisms’ impact on levothyroxine dose was studied in different populations.
Objective: To examine the association of the two single nucleotide polymorphism (SNP)s of deiodinase t
... Show MoreThis paper describes the problem of online autonomous mobile robot path planning, which is consisted of finding optimal paths or trajectories for an autonomous mobile robot from a starting point to a destination across a flat map of a terrain, represented by a 2-D workspace. An enhanced algorithm for solving the problem of path planning using Bacterial Foraging Optimization algorithm is presented. This nature-inspired metaheuristic algorithm, which imitates the foraging behavior of E-coli bacteria, was used to find the optimal path from a starting point to a target point. The proposed algorithm was demonstrated by simulations in both static and dynamic different environments. A comparative study was evaluated between the developed algori
... Show MoreThis paper includes the application of Queuing theory with of Particle swarm algorithm or is called (Intelligence swarm) to solve the problem of The queues and developed for General commission for taxes /branch Karkh center in the service stage of the Department of calculators composed of six employees , and it was chosen queuing model is a single-service channel M / M / 1 according to the nature of the circuit work mentioned above and it will be divided according to the letters system for each employee, and it was composed of data collection times (arrival time , service time, departure time)
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Cryptography is the process of transforming message to avoid an unauthorized access of data. One of the main problems and an important part in cryptography with secret key algorithms is key. For higher level of secure communication key plays an important role. For increasing the level of security in any communication, both parties must have a copy of the secret key which, unfortunately, is not that easy to achieve. Triple Data Encryption Standard algorithm is weak due to its weak key generation, so that key must be reconfigured to make this algorithm more secure, effective, and strong. Encryption key enhances the Triple Data Encryption Standard algorithm securities. This paper proposed a combination of two efficient encryption algorithms to
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