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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
Thu Apr 01 2021
Journal Name
Telkomnika (telecommunication Computing Electronics And Control)
Automatic human ear detection approach using modified adaptive search window technique
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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
Detection capability Alttafaria for some materials using a bacterial mutagenesis system
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Tested effective Alttafaria some materials used for different purposes, system a bacterial mutagenesis component of three bacterial isolates belonging to different races and materials tested included drug Briaktin

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Publication Date
Mon Apr 24 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Arabic Characters Recognition by Edge Detection Using Connected Component Contour(CO3)
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  In the present paper, Arabic Character Recognition  Edge detection method based on contour and connected components  is proposed. First stage contour extraction feature is introduced to tackle the Arabic characters edge detection problem, where the aim is to extract the edge information presented in the Arabic characters, since it is crucial to understand the character content.         The second stage connected components appling for the same characters to find edge detection. The proposed approach exploits a number of connected components, which move on the character by character intensity values, to establish matrix, which represents the edge information at each pixel location .

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Publication Date
Mon Jan 01 2018
Journal Name
Matec Web Of Conferences
Brain Tumour Detection using Fine-Tuning Mechanism for Magnetic Resonance Imaging
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In this paper, new brain tumour detection method is discovered whereby the normal slices are disassembled from the abnormal ones. Three main phases are deployed including the extraction of the cerebral tissue, the detection of abnormal block and the mechanism of fine-tuning and finally the detection of abnormal slice according to the detected abnormal blocks. Through experimental tests, progress made by the suggested means is assessed and verified. As a result, in terms of qualitative assessment, it is found that the performance of proposed method is satisfactory and may contribute to the development of reliable MRI brain tumour diagnosis and treatments.

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Publication Date
Thu Sep 15 2022
Journal Name
Knowledge And Information Systems
Multiresolution hierarchical support vector machine for classification of large datasets
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Support vector machine (SVM) is a popular supervised learning algorithm based on margin maximization. It has a high training cost and does not scale well to a large number of data points. We propose a multiresolution algorithm MRH-SVM that trains SVM on a hierarchical data aggregation structure, which also serves as a common data input to other learning algorithms. The proposed algorithm learns SVM models using high-level data aggregates and only visits data aggregates at more detailed levels where support vectors reside. In addition to performance improvements, the algorithm has advantages such as the ability to handle data streams and datasets with imbalanced classes. Experimental results show significant performance improvements in compa

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Publication Date
Fri Jul 01 2022
Journal Name
Iop Conference Series: Earth And Environmental Science
A study Some Technical Indicators of the Local Designed Machine
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Abstract<p>The effect of compound machine on wheat/ AlNoor cultivar was studied based on some technical indicators. were tested under three speeds ( 2.541, 3.433 and 4.091km.hr<sup>-1</sup>) and three tillage depths (14, 16 and 18cm). The experiments were conducted in a factorial experiment under complete randomized design with three replications. The results showed that the 2.541km.hr<sup>-1</sup> practical speed was significantly better than other two speed in all studied conditions. Except for the FC, which achieved the best results with the third speed 4.091 km.hr<sup>-1</sup>. mechanical parameters, plant growth parameters and yield and growth parameters. The 1</p> ... Show More
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Publication Date
Wed Jan 01 2020
Journal Name
Iraqi Journal Of Veterinary Sciences
Incidence of cutaneous and subcutaneous tumors of dogs from Baghdad city: Clinical, cytological and histopathological features
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The present study was conducted to estimate the incidence, clinical findings, cytological and histopathological characteristics of spontaneously occurring skin neoplasms in dogs. A total of 40 grossly suspected cases of cutaneous and subcutaneous tumors were gathered during the period from July 2016 to August 2018 from male and female dogs in Baghdad city. Dogs with skin neoplasia revealed various clinical signs, and their ages were older than 5 years to 15 years. German shepherd 30% followed by Terrier dogs 25% were more influenced than other breeds. Concerning tumor features, the majority of neoplasms had solitary lesion 70%, regular shapes 65% with black color 55%. The tumors frequently occurred on fore-limbs and abdomen, and 80% of them

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Publication Date
Thu Apr 07 2016
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
DETECTION OF MICROBIAL CONTAMINATION IN SOME TYPES OF FLOUR THAT AVAILABLE IN LOCAL MARKETS USING BACTRAC DEVICE 3400: DETECTION OF MICROBIAL CONTAMINATION IN SOME TYPES OF FLOUR THAT AVAILABLE IN LOCAL MARKETS USING BACTRAC DEVICE 3400
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A microbial study conducted for a number of flour samples (30 samples) Uses in the bakery ovens in various areas of the city of Baghdad, by used the conventional methods used in laboratories in microbial tests and compared with the modern techniqueby usedof BacTrac Device 3400 equipped from SY-LAB Impedance analysersAustrian company.The results of two ways showed (The conventional way and BacTrac Device test)that the total counts of aerobic bacteria, coliform bacteria, StaphylococcusSpp. bacteria, Bacillus cereus bacteria and yeasts and molds,Most of them were within the permissible borders in the Iraqi standard for grain and its products With free samples from SalmonellaSpp. bacteria, and that the screening by BacTrac device are shorten

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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Population Therapeutics And Clinical Pharmacology
Kinetic and thermodynamic study of adsorption of an industrial food dye using Iraqi clay
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Publication Date
Mon Mar 11 2019
Journal Name
Al-khwarizmi Engineering Journal
An Investigation Study of Tool Geometry in Single Point Incremental Forming (SPIF) and their effect on Residual Stresses Using ANOVA Model
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Incremental forming is a flexible sheet metal forming process which is performed by utilizing simple tools to locally deform a sheet of metal along a predefined tool path without using of dies. This work presents the single point incremental forming process for producing pyramid geometry and studies the effect of tool geometry, tool diameter, and spindle speed on the residual stresses. The residual stresses were measured by ORIONRKS 6000 test measuring instrument. This instrument was used with four angles of (0º,15º,30º, and 45º) and the average value of residual stresses was determined, the value of the residual stress in the original blanks was (10.626 MPa). The X-ray diffraction technology was used to measure the residual stresses

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