Preferred Language
Articles
/
joe-1666
An Empirical Investigation on Snort NIDS versus Supervised Machine Learning Classifiers
...Show More Authors

With the vast usage of network services, Security became an important issue for all network types. Various techniques emerged to grant network security; among them is Network Intrusion Detection System (NIDS). Many extant NIDSs actively work against various intrusions, but there are still a number of performance issues including high false alarm rates, and numerous undetected attacks. To keep up with these attacks, some of the academic researchers turned towards machine learning (ML) techniques to create software that automatically predict intrusive and abnormal traffic, another approach is to utilize ML algorithms in enhancing Traditional NIDSs which is a more feasible solution since they are widely spread. To upgrade the detection rates of current NIDSs, thorough analyses are essential to identify where ML predictors outperform them. The first step is to provide assessment of most used NIDS worldwide, Snort, and comparing its performance with ML classifiers. This paper provides an empirical study to evaluate performance of Snort and four supervised ML classifiers, KNN, Decision Tree, Bayesian net and Naïve Bays against network attacks, probing, Brute force and DoS. By measuring Snort metric, True Alarm Rate, F-measure, Precision and Accuracy and compares them with the same metrics conducted from applying ML algorithms using Weka tool. ML classifiers show an elevated performance with over 99% correctly classified instances for most algorithms, While Snort intrusion detection system shows a degraded classification of about 25% correctly classified instances, hence identifying Snort weaknesses towards certain attack types and giving leads on how to overcome those weaknesses. 

es.

Crossref
View Publication Preview PDF
Quick Preview PDF
Publication Date
Sun Nov 01 2020
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Utilizing the ATM technology in e-distance learning
...Show More Authors

<p>There is an Increasing demand for the education in the field of E-learning specially the higher education, and to keep contiuity between the user and the course director in any place and time. This research presents a proposed and simulation multimedia network design for distance learning utilizing ATM technique. The propsed framework determines the principle of ATM technology and shows how multimedia can be integrated within E- learning conteext. The first part of this research presents a theoretical design for the Electricity Department, university of technology. The purpose is to illustrate the usage of the ATM and Multimedia in distance learning process. In addition, this research composes two entities: Software entity

... Show More
View Publication
Scopus (9)
Crossref (1)
Scopus Crossref
Publication Date
Sat Dec 31 2022
Journal Name
International Journal On “technical And Physical Problems Of Engineering”
Age Estimation Utilizing Deep Learning Convolutional Neural Network
...Show More Authors

Estimating an individual's age from a photograph of their face is critical in many applications, including intelligence and defense, border security and human-machine interaction, as well as soft biometric recognition. There has been recent progress in this discipline that focuses on the idea of deep learning. These solutions need the creation and training of deep neural networks for the sole purpose of resolving this issue. In addition, pre-trained deep neural networks are utilized in the research process for the purpose of facial recognition and fine-tuning for accurate outcomes. The purpose of this study was to offer a method for estimating human ages from the frontal view of the face in a manner that is as accurate as possible and takes

... Show More
Scopus (13)
Scopus
Publication Date
Sun Jan 31 2016
Journal Name
International Journal Of Research In Humanities, Arts, And Literature
THE PROBLEMS FACING IRAQI CHILDREN IN LEARNING ENGLISH
...Show More Authors

DBN Rashid, IMPAT: International Journal of Research in Humanities, Arts, and Literature, 2016 - Cited by 5

View Publication
Publication Date
Sun Nov 14 2021
Journal Name
Palarch's Journal Of Archaeology Of Egypt/egyptology
Blended Learning in Teaching English to University Students
...Show More Authors

QJ Rashid, IH Abdul-Abbas, MR Younus, PalArch's Journal of Archaeology of Egypt/Egyptology, 2021 - Cited by 4

View Publication
Publication Date
Mon Jan 01 2024
Journal Name
Journal Of Engineering
Face-based Gender Classification Using Deep Learning Model
...Show More Authors

Gender classification is a critical task in computer vision. This task holds substantial importance in various domains, including surveillance, marketing, and human-computer interaction. In this work, the face gender classification model proposed consists of three main phases: the first phase involves applying the Viola-Jones algorithm to detect facial images, which includes four steps: 1) Haar-like features, 2) Integral Image, 3) Adaboost Learning, and 4) Cascade Classifier. In the second phase, four pre-processing operations are employed, namely cropping, resizing, converting the image from(RGB) Color Space to (LAB) color space, and enhancing the images using (HE, CLAHE). The final phase involves utilizing Transfer lea

... Show More
View Publication Preview PDF
Crossref (2)
Crossref
Publication Date
Wed Jun 01 2011
Journal Name
Journal Of Al-nahrain University Science
Breaking Knapsack Cipher Using Population Based Incremental Learning
...Show More Authors

View Publication
Crossref
Publication Date
Fri Sep 01 2023
Journal Name
Journal Of Engineering
Iraqi Sentiment and Emotion Analysis Using Deep Learning
...Show More Authors

Analyzing sentiment and emotions in Arabic texts on social networking sites has gained wide interest from researchers. It has been an active research topic in recent years due to its importance in analyzing reviewers' opinions. The Iraqi dialect is one of the Arabic dialects used in social networking sites, characterized by its complexity and, therefore, the difficulty of analyzing sentiment. This work presents a hybrid deep learning model consisting of a Convolution Neural Network (CNN) and the Gated Recurrent Units (GRU) to analyze sentiment and emotions in Iraqi texts. Three Iraqi datasets (Iraqi Arab Emotions Data Set (IAEDS), Annotated Corpus of Mesopotamian-Iraqi Dialect (ACMID), and Iraqi Arabic Dataset (IAD)) col

... Show More
View Publication Preview PDF
Crossref (7)
Crossref
Publication Date
Mon Jun 01 2020
Journal Name
Journal Of Engineering
Arabic Sentiment Analysis (ASA) Using Deep Learning Approach
...Show More Authors

Sentiment analysis is one of the major fields in natural language processing whose main task is to extract sentiments, opinions, attitudes, and emotions from a subjective text. And for its importance in decision making and in people's trust with reviews on web sites, there are many academic researches to address sentiment analysis problems. Deep Learning (DL) is a powerful Machine Learning (ML) technique that has emerged with its ability of feature representation and differentiating data, leading to state-of-the-art prediction results. In recent years, DL has been widely used in sentiment analysis, however, there is scarce in its implementation in the Arabic language field. Most of the previous researches address other l

... Show More
View Publication Preview PDF
Crossref (26)
Crossref
Publication Date
Mon Jan 01 2024
Journal Name
Lecture Notes On Data Engineering And Communications Technologies
Utilizing Deep Learning Technique for Arabic Image Captioning
...Show More Authors

View Publication
Scopus (3)
Crossref (2)
Scopus Crossref
Publication Date
Thu Dec 01 2016
Journal Name
Al.qadisiya Journal For The Sciences Of Physical Education
Comparing self-learning associated with the model and learning reverse fashioned way of partial way to learn Olympic lifts for beginners
...Show More Authors

Abstract The purpose of this study, teach the art of performing Olympic lifts (snatch and, clean and jerk) using the two methods are instructional (self-learning associated with the model) and (reverse style of partial way). Identify the effectiveness of these methods in learning the art of performance and style of the best Olympic lifting in the learning and retention of novice for Olympic lifts. The research sample consisted of 16 lifters were selected purposively representing specialist center for the care of athletic talent to weightlifting for ages 14 years. The sample was divided into two experimental, Each group (8) eight weightlifters. The experimental group used the style of the first self-learning associated with the m

... Show More
View Publication Preview PDF