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.

Scopus Crossref
View Publication Preview PDF
Quick Preview PDF
Publication Date
Thu Jul 02 2020
Journal Name
Jasep المجلة العربية للعلوم التربوية والنفسية
Critical Thinking-Based Learning: Developments, Trends, and Values
...Show More Authors

In recent years, English language teaching and second language acquisition has demonstrated a significant accentuation upon basic reasoning abilities improvement in the language capability advancement. Encouraging a point of view of duty to training basic intuition aptitudes in accordance with the English language courses, this paper gives an account of an investigation directed at theoretical meanings of basic deduction, drifts about the centrality of basic speculation for language educating and associations between critical thinking and language learning. The educators have the focal pretended by basic intuition in successful language teaching method, identified to Ennis’ (2011) critical thinking categories. The skill of thinking critic

... Show More
View Publication Preview PDF
Publication Date
Fri Jul 26 2024
Journal Name
Academia Open
Enhancing Pediatric Nursing Skills by Top Learning Strategies
...Show More Authors

Background: The efficacy of educational strategies is crucial for nursing students to competently perform pediatric procedures like nasogastric tube insertion. Specific Background: This study evaluates the effectiveness of simulation, blended, and self-directed learning strategies in enhancing these skills among nursing students. Knowledge Gap: Previous research lacks a comprehensive comparison of these strategies' impacts on skill development in pediatric nursing contexts. Aims: The study aims to assess the effectiveness of different educational strategies on nursing students' ability to perform pediatric nasogastric tube insertions. Methods: A pre-experimental design was employed at the College of Nursing, University of Baghdad, i

... Show More
View Publication
Crossref
Publication Date
Fri Mar 18 2022
Journal Name
Aro-the Scientific Journal Of Koya University
Detecting Deepfakes with Deep Learning and Gabor Filters
...Show More Authors

The proliferation of many editing programs based on artificial intelligence techniques has contributed to the emergence of deepfake technology. Deepfakes are committed to fabricating and falsifying facts by making a person do actions or say words that he never did or said. So that developing an algorithm for deepfakes detection is very important to discriminate real from fake media. Convolutional neural networks (CNNs) are among the most complex classifiers, but choosing the nature of the data fed to these networks is extremely important. For this reason, we capture fine texture details of input data frames using 16 Gabor filters indifferent directions and then feed them to a binary CNN classifier instead of using the red-green-blue

... Show More
View Publication
Scopus (12)
Crossref (4)
Scopus Clarivate Crossref
Publication Date
Mon Sep 30 2024
Journal Name
Al-mustansiriyah Journal Of Science
A Transfer Learning Approach for Arabic Image Captions
...Show More Authors

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
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
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
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
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 (14)
Scopus