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Development of an Optimized Botnet Detection Framework based on Filters of Features and Machine Learning Classifiers using CICIDS2017 Dataset
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Abstract<p>Botnet is a malicious activity that tries to disrupt traffic of service in a server or network and causes great harm to the network. In modern years, Botnets became one of the threads that constantly evolving. IDS (intrusion detection system) is one type of solutions used to detect anomalies of networks and played an increasing role in the computer security and information systems. It follows different events in computer to decide to occur an intrusion or not, and it used to build a strategic decision for security purposes. The current paper <italic>suggests</italic> a hybrid detection Botnet model using machine learning approach, performed and analyzed to detect Botnet attacks using CICIDS2017 dataset. The proposed model designed based on two types of filters to the botnet features; Correlation Attribute Eval and Principal Component deployed to reduce the dataset dimensions and to decrease the time complexity of the botnet detection process. The detection enhancement achieved by reducing the features of the dataset from 85 to 9. The training stage of classifiers is developed and compared based on six classifiers called (Random Forest, IBK, JRip, Multilayer Perceptron, Naive Bayes and OneR) evaluated to accomplish an optimized detection model. The performance and results of the proposed framework are validated using well-known metrics such as Accuracy (ACC), Precision (Pr), Recall (Rc) and F-Measure (F1). The consequence is that the combination of Correlation Attribute Eval (filter) with JRip (classifier) together can satisfy significant improvement in the Botnet detection process using CICIDS2017 dataset.</p>
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Publication Date
Fri Sep 15 2023
Journal Name
Journal Of Baghdad College Of Dentistry
Investigating the impact of non-nutritive sweeteners on the antifungal potential of alcoholic and aqueous Eucalyptus extracts against salivary candida albicans (An in-vitro study)
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Background: Eucalyptus extracts and derivatives are natural substances with potent antimicrobial properties. This study investigated the in- vitro effects of non-nutritive sweeteners on the antifungal activity of alcoholic and aqueous Eucalyptus extracts against Candida albicans, a common oral pathogen. Materials and Method: Ten isolates of Candida albicans were isolated from dental students’ salivary samples. The alcoholic and aqueous extracts were prepared from fresh Eucalyptus leaves using maceration. The sensitivity of Candida albicans isolates to various concentrations of Eucalyptus extracts ranging from 50 to 250 (mg/mL) was evaluated via agar well diffusion method, while the agar streaking method  was used to assess the minimum

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Publication Date
Thu Jun 27 2019
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
MICROFACIES ANALYSIS AND BASIN DEVELOPMENT OF THE CENOMANIAN - EARLY TURONIAN SEQUENCE IN THE RAFAI, NOOR AND HALFAYA OIL FIELDS, SOUTHEASTERN IRAQ
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    The stratigraphic sequence of Cenomanian-Early Turonian is composed of Ahmadi, Rumaila, and Mishrif formations in the Rifai, Noor and Halfaya Oil Fields within the Mesopotamian Zone of Iraq, which is bounded at top and bottom by unconformity surfaces. The microfacies analysis of the study wells assisted the recognition of five main environments (open marine, basinal, shallow open marine, Rudist biostrome, and lagoon); these microfacies were indicative of a normal lateral change facies from shallow water facies to deeper water and open marine sediments.

 

    Ahmadi Formation (Early Cenomanian) is characterized by open marine sediments during the transgressive conditions, and would be

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Publication Date
Sun Oct 02 2011
Journal Name
The Iraqi Journal Of Agricultural Sciences
AN ECONOMIC ANALYSIS OF PRODUCTION AND CONSUMPTION OF SUGAR CANE AND SUGAR BEET IN IRAQ
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In spite of economic importance of sugar cane and sugar beet as they described as industrial crops they still face decreasing rates of production and productivity in Iraq , and their production was not able to satisfy the local industrial demands for sugar . Thus this study aimed at studying and analyzing, production and productivity of sugar cane and sugar beet in Iraq and this has been done by using non serial data that can be obtained from official offices in Iraq . The area and production of sugar cane in Iraq recorded positive annual growth rates during 1970- 1978 which were 6% and 5% consequently , while the productivity of sugar cane recorded at the same duration of time negative annual growth rate which was 1% , while they recorded

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Publication Date
Fri Jan 01 2016
Journal Name
Journal Of College Of Education
An Investigative Study on the Electron Energy Distribution Function and Electron Transport Coefficients in SF6 -- Ne Gas Mixtures
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Publication Date
Thu Jun 01 2023
Journal Name
Iaes International Journal Of Artificial Intelligence (ij-ai)
Innovations in t-way test creation based on a hybrid hill climbing-greedy algorithm
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<p>In combinatorial testing development, the fabrication of covering arrays is the key challenge by the multiple aspects that influence it. A wide range of combinatorial problems can be solved using metaheuristic and greedy techniques. Combining the greedy technique utilizing a metaheuristic search technique like hill climbing (HC), can produce feasible results for combinatorial tests. Methods based on metaheuristics are used to deal with tuples that may be left after redundancy using greedy strategies; then the result utilization is assured to be near-optimal using a metaheuristic algorithm. As a result, the use of both greedy and HC algorithms in a single test generation system is a good candidate if constructed correctly. T

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Publication Date
Fri Mar 01 2019
Journal Name
Al-khwarizmi Engineering Journal
A New Fractal Printed Dipole Antenna Based on Tent Transformations for Wireless Communication Applications
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In this paper, a compact multiband printed dipole antenna is presented as a candidate for use in wireless communication applications. The proposed fractal antenna design is based on the second level tent transformation. The space-filling property of this fractal geometry permits producing longer lengths in a more compact size. Theoretical performance of this antenna has been calculated using the commercially available software IE3D from Zeland Software Inc. This electromagnetic simulator is based on the method of moments (MoM). The proposed dipole antenna has been found to possess a considerable size reduction compared with the conventional printed or wire dipole antenna designed at the same design frequency and using the same substrate

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Publication Date
Fri Jan 01 2021
Journal Name
Journal Of Engineering
A Proposed Adaptive Bitrate Scheme Based on Bandwidth Prediction Algorithm for Smoothly Video Streaming
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A robust video-bitrate adaptive scheme at client-aspect plays a significant role in keeping a good quality of video streaming technology experience. Video quality affects the amount of time the video has turned off playing due to the unfilled buffer state. Therefore to maintain a video streaming continuously with smooth bandwidth fluctuation, a video buffer structure based on adapting the video bitrate is considered in this work. Initially, the video buffer structure is formulated as an optimal control-theoretic problem that combines both video bitrate and video buffer feedback signals. While protecting the video buffer occupancy from exceeding the limited operating level can provide continuous video str

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Publication Date
Mon Jan 01 2024
Journal Name
Applied And Computational Mathematics
Reliable computational methods for solving Jeffery-Hamel flow problem based on polynomial function spaces
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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Exploring Important Factors in Predicting Heart Disease Based on Ensemble- Extra Feature Selection Approach
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Heart disease is a significant and impactful health condition that ranks as the leading cause of death in many countries. In order to aid physicians in diagnosing cardiovascular diseases, clinical datasets are available for reference. However, with the rise of big data and medical datasets, it has become increasingly challenging for medical practitioners to accurately predict heart disease due to the abundance of unrelated and redundant features that hinder computational complexity and accuracy. As such, this study aims to identify the most discriminative features within high-dimensional datasets while minimizing complexity and improving accuracy through an Extra Tree feature selection based technique. The work study assesses the efficac

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Publication Date
Fri Jul 19 2024
Journal Name
An International Journal Of Optimization And Control: Theories &amp; Applications (ijocta)
Design optimal neural network based on new LM training algorithm for solving 3D - PDEs
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In this article, we design an optimal neural network based on new LM training algorithm. The traditional algorithm of LM required high memory, storage and computational overhead because of it required the updated of Hessian approximations in each iteration. The suggested design implemented to converts the original problem into a minimization problem using feed forward type to solve non-linear 3D - PDEs. Also, optimal design is obtained by computing the parameters of learning with highly precise. Examples are provided to portray the efficiency and applicability of this technique. Comparisons with other designs are also conducted to demonstrate the accuracy of the proposed design.

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