Preferred Language
Articles
/
lBZirIoBVTCNdQwC8qJ0
Development of an Optimized Botnet Detection Framework based on Filters of Features and Machine Learning Classifiers using CICIDS2017 Dataset
...Show More Authors
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>
Scopus Crossref
View Publication
Publication Date
Thu Feb 01 2018
Journal Name
Journal Of Computational And Theoretical Nanoscience
Development of Wireless Controlling and Monitoring System for Robotic Hand Using Zigbee Protocol
...Show More Authors

Nowadays, the robotic arm is fast becoming the most popular robotic form used in the industry among others. Therefore, the issues regarding remote monitoring and controlling system are very important, which measures different environmental parameters at a distance away from the room and sets various condition for a desired environment through a wireless communication system operated from a central room. Thus, it is crucial to create a programming system which can control the movement of each part of the industrial robot in order to ensure it functions properly. EDARM ED-7100 is one of the simplest models of the robotic arm, which has a manual controller to control the movement of the robotic arm. In order to improve this control s

... Show More
View Publication
Scopus (5)
Crossref (4)
Scopus Crossref
Publication Date
Sun Apr 30 2023
Journal Name
Iraqi Journal Of Science
Review Study of E-Voting System Based on Smart Contracts Using Blockchain Technology
...Show More Authors

Voting is an important procedure in democratic societies in different countries, including Iraq. Electronic voting (E-voting) is becoming more prevalent due to reducing administrative costs and burdens. E-voting systems have many restrictions that affect the electoral process. For example, fraud, tampering with ballot boxes, taking many hours to announce results, and the difficulty of reaching polling stations. Over the last decade, blockchain and smart contract technologies have gained widespread adoption in various sectors, such as cryptocurrencies, finance, banking, and most notably in e-voting systems. If utilized properly, the developer demonstrates properties that are promising for their properties, such as security, privacy, trans

... Show More
View Publication Preview PDF
Scopus Crossref
Publication Date
Sun Jan 16 2022
Journal Name
Iraqi Journal Of Science
A Multi-Objective Evolutionary Algorithm based Feature Selection for Intrusion Detection
...Show More Authors

Nowad ays, with the development of internet communication that provides many facilities to the user leads in turn to growing unauthorized access. As a result, intrusion detection system (IDS) becomes necessary to provide a high level of security for huge amount of information transferred in the network to protect them from threats. One of the main challenges for IDS is the high dimensionality of the feature space and how the relevant features to distinguish the normal network traffic from attack network are selected. In this paper, multi-objective evolutionary algorithm with decomposition (MOEA/D) and MOEA/D with the injection of a proposed local search operator are adopted to solve the Multi-objective optimization (MOO) followed by Naï

... Show More
View Publication Preview PDF
Publication Date
Tue Jan 01 2019
Journal Name
Indian Journal Of Public Health Research &amp; Development
The Effect of Special Exercises for those with (Cognitive Concentration) in the Development of Motor Satisfaction and Learning Some Types of Scoring Basketball for Students
...Show More Authors

The importance of the research in the preparation of special exercises to develop some types of basketball scoring as a contribution to help the physical education teacher to find successful educational alternatives. The purpose of the study was to prepare special exercises for the cognitive (cognitive) survey in the development of motor satisfaction and learning some types of Scoring for basketball for students. Learn about the effect of cognitive exercises in cognitive development in students. The survey included students from the first stage of the Faculty of Physical Education and Sports Science \ University of Diyala (159) divided into 6 people. The sample was randomized by (b) and (b) D) and after dispersion by the standard method In

... Show More
View Publication
Scopus Crossref
Publication Date
Fri Sep 30 2022
Journal Name
Iraqi Journal Of Science
Improving Measurement of Effectiveness of Blended Learning in Iraqi Education Using SVM
...Show More Authors

E-learning has recently become of great importance, especially after the emergence of the Corona pandemic, but e-learning has many disadvantages. In order to preserve education, some universities have resorted to using blended learning. Currently, the Ministry of Higher Education and Scientific Research in Iraq has adopted e-learning in universities and schools, especially in scientific disciplines that need laboratories and a spatial presence. In this work, we collected a dataset based on 27 features and presented a model utilizing a support vector machine with regression that was enhanced with the KNN method, which identifies factors that have a substantial influence on the model for the type of education, whether blended or traditiona

... Show More
View Publication Preview PDF
Scopus (4)
Crossref (2)
Scopus Crossref
Publication Date
Thu Jan 01 2015
Journal Name
Journal Of Al-mansoor College
An Improvement to Face Detection Algorithm for Non-Frontal Faces
...Show More Authors

Publication Date
Sun Oct 30 2022
Journal Name
Iraqi Journal Of Science
An Improved Probability Density Function (PDF) for Face Skin Detection
...Show More Authors

      Face Detection by skin color in the field of computer vision is a difficult challenge. Detection of human skin focuses on the identification of pixels and skin-colored areas of a given picture. Since skin colors are invariant in orientation and size and rapid to process, they are used in the identification of human skin. In addition features like ethnicity, sensor, optics and lighting conditions that are different are sensitive factors for the relationship between surface colors and lighting (an issue that is strongly related to color stability). This paper presents a new technique for face detection based on human skin. Three methods of Probability Density Function (PDF) were applied to detect the face by skin color; these ar

... Show More
View Publication
Scopus (3)
Crossref (2)
Scopus Crossref
Publication Date
Fri Feb 08 2019
Journal Name
Iraqi Journal Of Laser
Photoacoustic Imaging for Tumor Detection: An in vitro Simulation Study
...Show More Authors

Photoacoustic is a unique imaging method that combines the absorption contrast of light or radio frequency waves with ultrasound resolution. When the deposition of this energy is sufficiently short, a thermo-elastic expansion takes place whereby acoustic waves are generated. These waves can be recorded and stored to construct an image. This work presents experimental procedure of laser photoacoustic two dimensional imaging to detect tumor embedded within normal tissue. The experimental work is accomplished using phantoms that are sandwiched from fish heart or blood sac (simulating a tumor) 1-14mm mean diameter embedded within chicken breast to simulate a real tissue. Nd: YAG laser of 1.064μm and 532nm wavelengths, 10ns pulse duration, 4

... Show More
View Publication Preview PDF
Publication Date
Tue Jan 17 2017
Journal Name
International Journal Of Science And Research (ijsr)
Detection System of Varicose Disease using Probabilistic Neural Network
...Show More Authors

Publication Date
Fri Jun 24 2022
Journal Name
Iraqi Journal Of Science
Using PCR for detection of cutaneous leishmaniasis in Baghdad
...Show More Authors

Cutaneous Leishmaniasis (CL) is an endemic disease and one of the major health problems in Iraq. Leishmania tropica is known as the causative agent of Cutaneous Leishmaniasis in Baghdad.The classical serological methods of diagnosing leishmaniasis is a poor sensitivity especially for the sub genus and time consuming Here we have investigated two primer pairs, one specific for Leishmania as genus and the primer specific for the species of L. tropica to be detected by polymerase chain reaction (PCR).Samples were collected from (AL-karama Teaching Hospital) and whole genomic DNA was extracted from axenic promastigotes.The extracted DNA was amplified by PCRwith two KDNA primer pairs, for genus specific (13A/13B) and (Lmj4/Uni21) to identify

... Show More
View Publication Preview PDF